阅读说明：本技术 一种媒体特征的比对方法及装置 (Media feature comparison method and device ) 是由 何轶 李磊 杨成 李�根 李亦锬 于 2018-03-29 设计创作，主要内容包括：本公开涉及一种媒体特征的比对方法及装置,该方法包括：获取第一媒体对象的第一媒体特征序列和第二媒体对象的第二媒体特征序列,所述第一媒体特征序列包含顺序排列的多个第一媒体特征单体,所述第二媒体特征序列包含顺序排列的多个第二媒体特征单体；确定所述第一媒体特征单体与所述第二媒体特征单体之间的单体相似度；根据所述单体相似度确定所述第一媒体特征序列与所述第二媒体特征序列之间的相似度矩阵；根据所述相似度矩阵确定所述第一媒体对象与所述第二媒体对象的相似情况。(The disclosure relates to a media feature comparison method and a device, wherein the method comprises the following steps: acquiring a first media characteristic sequence of a first media object and a second media characteristic sequence of a second media object, wherein the first media characteristic sequence comprises a plurality of first media characteristic monomers which are sequentially arranged, and the second media characteristic sequence comprises a plurality of second media characteristic monomers which are sequentially arranged; determining a monomer similarity between the first media feature monomer and the second media feature monomer; determining a similarity matrix between the first media feature sequence and the second media feature sequence according to the single similarity; and determining the similarity of the first media object and the second media object according to the similarity matrix.)

1. A method of media feature alignment, the method comprising:

Acquiring a first media characteristic sequence of a first media object and a second media characteristic sequence of a second media object, wherein the first media characteristic sequence comprises a plurality of first media characteristic monomers which are sequentially arranged, and the second media characteristic sequence comprises a plurality of second media characteristic monomers which are sequentially arranged;

Determining a monomer similarity between the first media feature monomer and the second media feature monomer;

Determining a similarity matrix between the first media feature sequence and the second media feature sequence according to the single similarity;

And determining the similarity of the first media object and the second media object according to the similarity matrix.

2. The method for matching media characteristics according to claim 1,

The first media feature singleton and the second media feature singleton are floating point features;

the determining the monomer similarity between the first media feature monomer and the second media feature monomer comprises:

And determining the monomer similarity according to the cosine distance between the first media characteristic monomer and the second media characteristic monomer.

3. The method for matching media characteristics according to claim 1,

The first media characteristic monomer and the second media characteristic monomer are of binary characteristics and have the same characteristic monomer length;

The determining the monomer similarity between the first media feature monomer and the second media feature monomer comprises:

And determining the monomer similarity according to the Hamming distance between the first media feature monomer and the second media feature monomer.

4. The method for matching media characteristics according to claim 1,

The acquiring of the first media feature sequence of the first media object and the second media feature sequence of the second media object comprises acquiring a plurality of types of the first media feature sequence of the first media object and acquiring a plurality of types of the second media feature sequence of the second media object;

The determining of the monomer similarity between the first media characteristic monomer and the second media characteristic monomer comprises determining the monomer similarity between the first media characteristic monomer and the second media characteristic monomer of the same type respectively to obtain a plurality of monomer similarities;

The determining the similarity matrix between the first media feature sequence and the second media feature sequence according to the individual similarity includes determining an average value or a minimum value of the multiple individual similarities, and determining the similarity matrix according to the average value or the minimum value of the multiple individual similarities.

5. the method for aligning media characteristics according to claim 1, wherein the plurality of first media characteristic monomers are arranged in the first media characteristic sequence in a chronological order, and the plurality of second media characteristic monomers are arranged in the second media characteristic sequence in a chronological order.

6. The method for comparing media characteristics according to claim 5, wherein one point in the similarity matrix corresponds to one of the monomer similarities; the points of the similarity matrix are arranged in the horizontal direction according to the sequence of the first media feature monomers in the first media feature sequence, and are arranged in the vertical direction according to the sequence of the second media feature monomers in the second media feature sequence.

7. The method for comparing media characteristics according to claim 6, wherein the determining the similarity between the first media object and the second media object according to the similarity matrix comprises: and determining the similarity degree and the matching segment of the first media object and the second media object according to the straight line in the similarity matrix.

8. the method for comparing media characteristics according to claim 7, wherein the determining the similarity between the first media object and the second media object according to the straight line in the similarity matrix comprises:

Defining a plurality of lines with the slope as a preset slope set value as alternative lines, and determining the line similarity of the alternative lines according to the average value or the sum value of the monomer similarity contained in each alternative line;

Selecting one alternative straight line which enables the straight line similarity to be maximum from the multiple alternative straight lines, and defining the alternative straight line as a first matching straight line;

Determining the similarity degree of the first media object and the second media object according to the straight line similarity of the first matching straight line; and determining the starting and ending time of the matching segments of the first media object and the second media object according to the starting point and the ending point of the first matching straight line.

9. the method for comparing media characteristics according to claim 8, wherein the slope setting values are a plurality of values, and the alternative line is a line having a slope of any one of the slope setting values.

10. The method for comparing media characteristics according to claim 6, wherein the determining the similarity between the first media object and the second media object according to the similarity matrix comprises:

Selecting a plurality of points which enable the monomer similarity to be maximum in the similarity matrix as similarity extreme points;

Fitting a straight line in the similarity matrix as a second matching straight line based on the plurality of extreme similarity points;

Determining the similarity degree of the first media object and the second media object according to the average value or the total value of the single similarity degree contained in the second matching straight line; and determining the starting and ending time of the matching segments of the first media object and the second media object according to the starting point and the ending point of the second matching straight line.

11. The method for media feature matching according to claim 10, wherein the fitting a straight line in the similarity matrix as a second matching straight line based on the extreme similarity points comprises: and fitting a straight line with a slope being a preset slope set value or a slope close to the preset slope set value in the similarity matrix by using a random sampling consistency method to serve as a second matching straight line.

12. The method for comparing media characteristics according to claim 8 or 10, wherein the determining the similarity between the first media object and the second media object according to the similarity matrix further comprises:

judging whether the starting point and the ending point of the first matching straight line or the second matching straight line reach a preset monomer similarity set value or not, removing the part of the starting point and the ending point which does not reach the monomer similarity set value, and reserving a middle section of straight line and defining the middle section of straight line as a third matching straight line;

And determining the similarity degree of the first media object and the second media object according to the straight line similarity of the third matching straight line, and determining the starting and ending time of the matching segment according to the starting point and the ending point of the third matching straight line.

13. An apparatus for matching media features, the apparatus comprising:

A media feature sequence obtaining module, configured to obtain a first media feature sequence of a first media object and a second media feature sequence of a second media object, where the first media feature sequence includes a plurality of first media feature monomers that are sequentially arranged, and the second media feature sequence includes a plurality of second media feature monomers that are sequentially arranged;

A monomer similarity determination module, configured to determine a monomer similarity between the first media feature monomer and the second media feature monomer;

A similarity matrix determining module, configured to determine a similarity matrix between the first media feature sequence and the second media feature sequence according to the individual similarity;

And the similar situation determining module is used for determining the similar situation of the first media object and the second media object according to the similarity matrix.

14. The apparatus for matching media characteristics according to claim 13, further comprising a module for performing the steps of any one of claims 2 to 12.

15. a media feature comparison hardware apparatus, comprising:

a memory for storing non-transitory computer readable instructions; and

a processor for executing the computer readable instructions, such that the processor when executing implements the method for matching media features according to any one of claims 1 to 12.

16. A computer-readable storage medium storing non-transitory computer-readable instructions which, when executed by a computer, cause the computer to perform the method of alignment of media features of any one of claims 1 to 12.

17. a terminal device comprising the apparatus for comparing media characteristics of claim 13 or 14.

Technical Field

the present disclosure relates to the field of media processing technologies, and in particular, to a method and an apparatus for comparing media characteristics.

Background

Media features such as video features and audio features (or referred to as media fingerprints), and media feature comparison and media feature retrieval are widely applied in the current multimedia information society. By utilizing the media characteristic comparison, repeated uploading of videos and audios can be avoided, further embezzlement of the media is prevented, storage of the media is optimized, and in addition, media content monitoring, copyright detection and the like can be carried out by utilizing the media characteristic comparison.

The existing media characteristic comparison method has the problems of poor accuracy and low efficiency, which causes huge consumption on operation resources and storage resources.

Disclosure of Invention

The present disclosure is directed to a method and an apparatus for comparing media characteristics.

the purpose of the present disclosure is achieved by the following technical means. The media characteristic comparison method provided by the present disclosure includes the following steps: acquiring a first media characteristic sequence of a first media object and a second media characteristic sequence of a second media object, wherein the first media characteristic sequence comprises a plurality of first media characteristic monomers which are sequentially arranged, and the second media characteristic sequence comprises a plurality of second media characteristic monomers which are sequentially arranged; determining a monomer similarity between the first media feature monomer and the second media feature monomer; determining a similarity matrix between the first media feature sequence and the second media feature sequence according to the single similarity; and determining the similarity of the first media object and the second media object according to the similarity matrix.

The object of the present disclosure can be further achieved by the following technical measures.

in the method for comparing media characteristics, the first media characteristic unit and the second media characteristic unit are floating point characteristics; the determining the monomer similarity between the first media feature monomer and the second media feature monomer comprises: and determining the monomer similarity according to the cosine distance between the first media characteristic monomer and the second media characteristic monomer.

In the method for comparing media characteristics, the first media characteristic monomer and the second media characteristic monomer are binary characteristics and have the same characteristic monomer length; the determining the monomer similarity between the first media feature monomer and the second media feature monomer comprises: and determining the monomer similarity according to the Hamming distance between the first media feature monomer and the second media feature monomer.

the method for comparing media characteristics described above, wherein the obtaining a first media characteristic sequence of a first media object and a second media characteristic sequence of a second media object includes obtaining a plurality of types of the first media characteristic sequences of the first media object and obtaining a plurality of types of the second media characteristic sequences of the second media object; the determining of the monomer similarity between the first media characteristic monomer and the second media characteristic monomer comprises determining the monomer similarity between the first media characteristic monomer and the second media characteristic monomer of the same type respectively to obtain a plurality of monomer similarities; the determining the similarity matrix between the first media feature sequence and the second media feature sequence according to the individual similarity includes determining an average value or a minimum value of the multiple individual similarities, and determining the similarity matrix according to the average value or the minimum value of the multiple individual similarities.

In an embodiment of the present invention, the plurality of first media feature monomers are arranged in the first media feature sequence in a time sequence, and the plurality of second media feature monomers are arranged in the second media feature sequence in a time sequence.

In the method for comparing media characteristics, one point in the similarity matrix corresponds to one monomer similarity; the points of the similarity matrix are arranged in the horizontal direction according to the sequence of the first media feature monomers in the first media feature sequence, and are arranged in the vertical direction according to the sequence of the second media feature monomers in the second media feature sequence.

The method for comparing media characteristics, wherein the determining the similarity between the first media object and the second media object according to the similarity matrix includes: and determining the similarity degree and the matching segment of the first media object and the second media object according to the straight line in the similarity matrix.

In the method for comparing media characteristics, determining the similarity between the first media object and the second media object according to the straight line in the similarity matrix includes: defining a plurality of lines with the slope as a preset slope set value as alternative lines, and determining the line similarity of the alternative lines according to the average value or the sum value of the monomer similarity contained in each alternative line; selecting one alternative straight line which enables the straight line similarity to be maximum from the multiple alternative straight lines, and defining the alternative straight line as a first matching straight line; determining the similarity degree of the first media object and the second media object according to the straight line similarity of the first matching straight line; and determining the starting and ending time of the matching segments of the first media object and the second media object according to the starting point and the ending point of the first matching straight line.

In the aforementioned method for comparing media characteristics, the slope setting value is multiple, and the alternative line is a line whose slope is any one of the multiple slope setting values.

The method for comparing media characteristics, wherein the determining the similarity between the first media object and the second media object according to the similarity matrix includes: selecting a plurality of points which enable the monomer similarity to be maximum in the similarity matrix as similarity extreme points; fitting a straight line in the similarity matrix as a second matching straight line based on the plurality of extreme similarity points; determining the similarity degree of the first media object and the second media object according to the average value or the total value of the single similarity degree contained in the second matching straight line; and determining the starting and ending time of the matching segments of the first media object and the second media object according to the starting point and the ending point of the second matching straight line.

The media feature comparison method, wherein fitting a straight line in the similarity matrix as a second matching straight line based on the plurality of extreme similarity points includes: and fitting a straight line with a slope being a preset slope set value or a slope close to the preset slope set value in the similarity matrix by using a random sampling consistency method to serve as a second matching straight line.

the method for comparing media characteristics described above, wherein the determining the similarity between the first media object and the second media object according to the similarity matrix further includes: judging whether the starting point and the ending point of the first matching straight line or the second matching straight line reach a preset monomer similarity set value or not, removing the part of the starting point and the ending point which does not reach the monomer similarity set value, and reserving a middle section of straight line and defining the middle section of straight line as a third matching straight line; and determining the similarity degree of the first media object and the second media object according to the straight line similarity of the third matching straight line, and determining the starting and ending time of the matching segment according to the starting point and the ending point of the third matching straight line.

The purpose of the present disclosure is also achieved by the following technical solutions. According to the media characteristic comparison device provided by the present disclosure, the device comprises: a media feature sequence obtaining module, configured to obtain a first media feature sequence of a first media object and a second media feature sequence of a second media object, where the first media feature sequence includes a plurality of first media feature monomers that are sequentially arranged, and the second media feature sequence includes a plurality of second media feature monomers that are sequentially arranged; a monomer similarity determination module, configured to determine a monomer similarity between the first media feature monomer and the second media feature monomer; a similarity matrix determining module, configured to determine a similarity matrix between the first media feature sequence and the second media feature sequence according to the individual similarity; and the similar situation determining module is used for determining the similar situation of the first media object and the second media object according to the similarity matrix.

The object of the present disclosure can be further achieved by the following technical measures.

The device for comparing media characteristics further comprises a module for executing the steps of the method for comparing any one of the media characteristics.

The purpose of the present disclosure is also achieved by the following technical solutions. According to the present disclosure, a media feature comparison hardware device includes: a memory for storing non-transitory computer readable instructions; and the processor is used for executing the computer readable instructions, so that the processor realizes the comparison method of any one of the media characteristics when executing.

The purpose of the present disclosure is also achieved by the following technical solutions. According to the present disclosure, a terminal device includes any one of the media feature comparison devices.

The purpose of the present disclosure is also achieved by the following technical solutions. A computer-readable storage medium according to the present disclosure is provided for storing non-transitory computer-readable instructions, which when executed by a computer, cause the computer to perform any one of the aforementioned methods for media feature comparison.

The foregoing is a summary of the present disclosure, and for the purposes of promoting a clear understanding of the technical means of the present disclosure, the present disclosure may be embodied in other specific forms without departing from the spirit or essential attributes thereof.

Drawings

fig. 1 is a flow chart of a method for comparing media characteristics according to an embodiment of the disclosure.

Fig. 2 is a schematic grayscale diagram corresponding to a similarity matrix according to an embodiment of the disclosure.

fig. 3 is a block diagram of a comparison process using a dynamic programming method according to an embodiment of the disclosure.

Fig. 4 is a block diagram of a comparison process using a uniform velocity media method according to an embodiment of the disclosure.

Fig. 5 is a block diagram of a process for determining a similarity matrix based on a plurality of types of media feature sequences according to an embodiment of the present disclosure.

fig. 6 is a block diagram of a media feature matching apparatus according to an embodiment of the disclosure.

fig. 7 is a block diagram of a similarity determination module according to an embodiment of the present disclosure.

Fig. 8 is a block diagram of a similar situation determining module according to another embodiment of the present disclosure.

Fig. 9 is a block diagram of a media feature comparison apparatus for determining a similarity matrix based on sequences of multiple types of media features according to an embodiment of the present disclosure.

Fig. 10 is a hardware block diagram of a media feature comparison hardware device according to an embodiment of the disclosure.

FIG. 11 is a schematic diagram of a computer-readable storage medium of one embodiment of the present disclosure.

Fig. 12 is a block diagram of a terminal device according to an embodiment of the present disclosure.

Detailed Description

To further explain the technical means and effects of the present disclosure adopted to achieve the intended purpose, the following detailed description will be given of specific embodiments, structures, features and effects of the media feature comparison method and device according to the present disclosure with reference to the accompanying drawings and preferred embodiments.

fig. 1 is a schematic flow chart diagram of an embodiment of a media feature comparison method according to the present disclosure. Referring to fig. 1, the method for comparing media characteristics of the present disclosure mainly includes the following steps:

Step S10, a media feature sequence of the first media object is obtained as a first media feature sequence, and a media feature sequence of the second media object is obtained as a second media feature sequence. The first media object and the second media object are two media to be compared, and may be various types of media such as audio, video, multiple continuously shot photos, and the like. The media feature sequence may be an audio feature, a video feature, an image feature, or the like, and the video object may be actually aligned by acquiring the audio feature of the video object according to the method of the present disclosure.

Specifically, the first media feature sequence includes a plurality of first media feature monomers arranged in sequence, and the second media feature sequence includes a plurality of second media feature monomers arranged in sequence, where it is not assumed that lengths of the first media feature sequence and the second media feature sequence are M₁And M₂Wherein M is₁And M₂is a positive integer, i.e. the first sequence of media characteristics contains M₁A first media feature monomer, a second media feature sequence containing M₂A second media feature cell. Thereafter, the process proceeds to step S20.

Further, in some embodiments, the order is arranged that the plurality of first/second media feature monomers in the first/second media feature sequence are arranged in chronological order: for example, in the process of extracting media features in advance, frames are extracted from a media object, a media feature monomer is generated according to each frame, so that each media feature monomer corresponds to each frame of the media object, and then the media feature monomers are arranged according to the time sequence of each frame in the media object to obtain a media feature sequence. Therefore, the aforementioned media feature list may also be referred to as a frame feature, and the aforementioned media feature sequence may also be referred to as a media feature.

It should be noted that, the method for extracting the media feature sequence and the type of the media feature sequence are not limited, but the first media feature sequence and the second media feature sequence should be the same type of media features obtained by the same feature extraction method. In one example of the disclosure, floating-point feature sequences of the first media object and the second media object may be obtained simultaneously as the first media feature sequence and the second media feature sequence, and each media feature monomer in the floating-point feature sequences is a floating-point number. In another example, the binary number feature sequence of the first media object and the binary number feature sequence of the second media object may be obtained simultaneously, or the obtained other type of media features may be binarized to obtain the binary number feature sequence. Each feature monomer in the binary number feature sequence is a bit string composed of 0/1, and the media feature monomers extracted by the same method have the same length (or called bit number).

Step S20, determining the monomer similarity between each first media characteristic monomer and each second media characteristic monomer to obtain M₁×M₂Individual monomer similarity. Each monomer similarity is used to indicate the degree of similarity between two media feature monomers, and specifically, the greater the monomer similarity, the more similar the media feature monomers. Thereafter, the process proceeds to step S30.

Specifically, a distance or a metric capable of determining the degree of similarity between two media features may be selected as the single similarity according to the type of the media features.

in an embodiment of the disclosure, when the first media feature sequence and the second media feature sequence are floating-point features at the same time, the single similarity may be determined according to a cosine distance (or called as cosine similarity) between the first media feature single and the second media feature single; the cosine distance can generally be directly determined as the monomer similarity.

In an embodiment of the disclosure, when the first media feature sequence and the second media feature sequence are binary number features at the same time, the monomer similarity may be determined according to a Hamming distance (Hamming distance) between the first media feature monomer and the second media feature monomer. Specifically, a Hamming distance (Hamming distance) between a first media feature monomer and a second media feature monomer is calculated, then a difference between a feature monomer length (bit number) and the Hamming distance is calculated, and a ratio of the difference to the feature monomer length is determined as a monomer similarity to represent a proportion of the same bit in two binary features. The hamming distance is a common measurement in the field of information theory, and the hamming distance between two equal-length character strings is the number of different characters at the corresponding positions of the two character strings. When the hamming distance is actually calculated, the xor operation can be performed on the two character strings, and the number of 1 is counted, which is the hamming distance.

it should be noted that the monomer similarity is not limited to the cosine distance or the hamming distance, but any distance or measure that can determine the similarity between two media feature monomers can be used.

It should be noted that the individual similarity may also be referred to as inter-frame similarity if each individual media feature corresponds to each frame of the media object.

Step S30, determining a Similarity Matrix (Similarity Matrix) between the first media feature sequence and the second media feature sequence according to the individual Similarity.

Specifically, each point in the similarity matrix corresponds to a single similarity, so that the similarity matrix records the single similarity between each first media feature single and each second media feature single. And, each point of the similarity matrix: the first media feature monomers are arranged in the first media feature sequence in the transverse direction, and the second media feature monomers are arranged in the second media feature sequence in the longitudinal direction. So that the point at the ith row and the jth column represents the monomer similarity between the ith first media characteristic monomer of the first media object and the jth second media characteristic monomer of the second media object, and the similarity matrix is M₁×M₂And (4) matrix. Thereafter, the process proceeds to step S40.

For convenience of visualization, the similarity matrix may be converted into a gray scale diagram as shown in fig. 2, the gray scale of each point is used to represent the magnitude of the single similarity at the corresponding position in the similarity matrix. Specifically, if the gray scale of a point is closer to white, it indicates that the monomer similarity corresponding to the point is higher, for example, the point marked as I in fig. 2; and if the gray scale of a point is closer to black, it means that the single body similarity corresponding to the point is lower, for example, the point at II marked in fig. 2.

In actual practice, instead of first calculating the similarity of each individual unit in step S20 and then determining the similarity matrix in step S30, the similarity matrix may be directly determined, and the similarity of each individual unit may be calculated in the process of determining each point of the similarity matrix.

Step S40, determining the similarity between the first media object and the second media object according to the similarity matrix. Specifically, the so-called determination of similarity includes: determining the similarity degree of the first media object and the second media object according to the similarity matrix, expressing the similarity degree by using the comparison score, and/or determining the starting and ending time of the matching segments of the first media object and the second media object according to the similarity matrix. Wherein, the comparison score can be a score between 0 and 1, and a larger number indicates that the two media objects are more similar.

According to the media characteristic comparison method, the similarity between the media objects is determined based on the similarity matrix between the two media objects, and the efficiency and the accuracy of media comparison can be improved.

In some embodiments of the present disclosure, step S40 includes: and determining the similarity of the first media object and the second media object according to the straight line in the similarity matrix.

It should be noted that since a media feature sequence generally includes a finite number of media feature monomers, the similarity matrix is a finite matrix, and thus, in practice, a so-called "straight line" is a finite long line segment composed of a plurality of points in the similarity matrix. The line has a slope that is the slope of a line connecting the plurality of points comprised by the line. In addition, the start point and the end point of the straight line may be any point in the similarity matrix, and need not be points located at the edge.

The straight lines referred to in the present disclosure include a diagonal line in the similarity matrix, each line segment parallel to the diagonal line, the straight lines having a slope of 1 from top left to bottom right in the similarity matrix (e.g., the straight line III marked in fig. 2), and the straight lines having a slope different from 1. For example, a straight line with a slope close to 1 may be used to improve the robustness of the media alignment; may be a straight line with a slope of 2,3,. or 1/2, 1/3,. etc., to account for the alignment of the paced media objects; and may even be a straight line with a negative slope (a straight line from the bottom left to the top right in the similarity matrix) to cope with a media object subjected to the reverse play processing. The diagonal line is a line segment (actually, a straight line with a slope of 1 starting from the point at the upper left corner) consisting of points located at (1,1), (2,2), (3,3).

In fact, each straight line in the similarity matrix is composed of a plurality of sequentially arranged single similarity degrees, so that each straight line represents the similar situation of a plurality of sequentially arranged media feature single pairs, and the similarity degree of a section of first media object segment and a section of second media object segment can be represented. Wherein each media feature cell pair comprises a first media feature cell and a second media feature cell. That is, each line represents a degree of similarity between a plurality of sequentially arranged first media characteristic singles and a plurality of sequentially arranged second media characteristic singles. The slope of the straight line and the starting point and the ending point show the length and the position of the two media segments. For example, a straight line formed by (1,1), (2,3), (3,5) and (4,7) represents the similarity between the first media feature cell with the ordinal number 1 and the second media feature cell with the ordinal number 1, and the similarity between the first media feature cell with the ordinal number 2 and the second media feature cell with the ordinal number 3.

Thus, the similarity of two media objects can be determined from the straight lines in the similarity matrix: defining the average (or overall) of the similarity of the individual media contained in a straight line as the straight line similarity of the straight line, where the straight line similarity can represent the similarity between the corresponding first media feature individual and the corresponding second media feature individual; determining a straight line with the highest straight line similarity in the similarity matrix, wherein the straight line is not called a matching straight line; and determining the straight line similarity of the matching straight lines as the similarity degree of the first media object and the second media object, and/or determining the matching segments of the first media object and the second media object according to a plurality of first media feature monomers and a plurality of second media feature monomers corresponding to the matching straight lines.

The specific method for determining the matching segments according to the straight lines (e.g. matching straight lines) in the similarity matrix may be: determining the starting time of the matching segment in the first media object according to the ordinal number (or abscissa in the similarity matrix) of the first media feature monomer corresponding to the starting point of the straight line, and determining the starting time of the matching segment in the second media object according to the ordinal number (or ordinate in the similarity matrix) of the second media feature monomer corresponding to the starting point; similarly, the end time of the matching segment in the first media object is determined from the abscissa of the end point of the straight line, while the end time of the matching segment in the second media object is determined from the ordinate of the end point.

it should be noted that, in the process of determining the matching straight line, a straight line with the highest straight line similarity may be determined from a plurality of preset straight lines, for example, the preset straight lines are all straight lines with slopes of preset slope setting values (for example, the slopes are 1), or a plurality of points which are selected from the similarity matrix and make the single body similarity rank forward may be selected, and then a straight line may be fitted according to the points, so as to generate a straight line which makes the straight line similarity relatively highest.

According to the media characteristic comparison method, the similarity degree and/or the matching segment of the two media objects are determined according to the straight line in the similarity matrix, and the efficiency and the accuracy of media comparison can be greatly improved.

In a specific embodiment of the present disclosure, a dynamic programming method may be utilized to determine the similarity of two media objects according to the similarity matrix. Fig. 3 is a schematic flow chart diagram of a comparison performed by using a dynamic programming method according to an embodiment of the present disclosure. Referring to fig. 3, in an embodiment, the step S40 of the present disclosure includes the following specific steps:

Step S41a, defining a plurality of straight lines with a preset slope setting value as candidate straight lines, and determining the straight line similarity of each candidate straight line according to the monomer similarity included in the candidate straight line. Specifically, the straight line similarity of a straight line may be set as an average value of the individual monomer similarities included in the straight line, or may be set as a total value of the individual monomer similarities included in the straight line. In one specific example, the slope setting value may be taken to be 1, i.e. the aforementioned alternative straight line is: a diagonal line in the similarity matrix and a line parallel to the diagonal line. Thereafter, the process proceeds to step S41 b.

It should be noted that, in an embodiment of the present disclosure, step S41a further includes: those straight lines that include monomer similarities less than the preset straight line length setting value are excluded from the candidate straight lines, and the process then proceeds to step S41 b. Alternatively, in this embodiment, the alternative straight line further satisfies: the number of monomer similarities contained reaches a preset linear length set value. By excluding the straight line with too little monomer similarity, the problem that the accuracy of the finally obtained comparison result is affected by too little monomer similarity included in the straight line can be excluded.

In step S41b, a candidate straight line that maximizes the similarity of the straight lines is determined from the plurality of candidate straight lines, and is defined as a first matching straight line. Thereafter, the process proceeds to step S41 c.

Step S41c, determining the straight line similarity of the first matching straight line as a comparison score for representing the similarity between the first media object and the second media object; and determining the starting and ending time of the matching segments in the two media objects according to the starting point and the ending point of the first matching straight line.

It should be noted that, in some embodiments of the present disclosure, the preset slope setting value in step S41a may be multiple, that is, the alternative straight line is a straight line with a slope equal to any one of the multiple slope setting values, for example, the alternative straight line may be a straight line with a slope of 1, -1, 2, 1/2, etc., and in step S41b, a first matching straight line is determined from the multiple alternative straight lines with a slope of any one of the multiple slope setting values.

According to the media characteristic comparison method, the comparison score and/or the matched media segment are/is determined by using a dynamic programming method, so that the comparison accuracy and the comparison speed can be improved.

In another embodiment of the present disclosure, a uniform velocity media method may also be used to determine the similarity between two media objects according to the similarity matrix. Fig. 4 is a schematic flow chart diagram of comparison using a uniform velocity media method according to an embodiment of the present disclosure. Referring to fig. 4, in an embodiment, the step S40 of the present disclosure includes the following specific steps:

In step S42a, a plurality of points with the highest single similarity are selected from the similarity matrix and defined as the similarity extreme points. The specific number of similarity extreme points taken may be preset. Thereafter, the process proceeds to step S42 b.

in step S42b, a straight line is fitted in the similarity matrix as a second matching straight line based on the plurality of extreme similarity points. In some specific examples, a straight line having a preset slope setting value or a slope close to the preset slope setting value is fitted as the second matching straight line based on the plurality of similarity extreme points, for example, a straight line having a slope close to 1 is fitted. Specifically, a straight line with a slope close to a slope set value may be fitted in the similarity matrix by using a Random Sample Consensus method (RANSAC method). The RANSAC method is a commonly used method for calculating mathematical model parameters of data according to a set of sample data sets containing abnormal data to obtain valid sample data. Thereafter, the process proceeds to step S42 c.

Step S42c, determining a comparison score according to the similarity of the single bodies included in the second matching straight line, so as to represent the similarity between the first media object and the second media object. Specifically, the average value of the individual monomer similarities on the second matching straight line may be determined as the alignment score. In addition, the start and end times of the matching segments in the two media objects may be determined from the start and end points of the second matching straight line.

According to the media characteristic comparison method, the comparison score and/or the matched media segments are/is determined by utilizing a uniform-speed media method, so that the comparison accuracy and the comparison speed can be improved.

In some embodiments of the present disclosure (e.g., the aforementioned embodiments shown in fig. 3 and 4), step S40 further includes: detecting the beginning part and the ending part of the obtained first matching straight line or the second matching straight line, judging whether the points (monomer similarity) of the beginning part and the ending part of the first matching straight line/the second matching straight line reach a preset monomer similarity set value or not, removing the parts of the beginning part and the ending part of the first matching straight line/the second matching straight line which do not reach the monomer similarity set value (namely the monomer similarity is not high), and reserving a middle section of straight line and defining as a third matching straight line; and determining the similarity degree of the first media object and the second media object according to the straight line similarity of the third matching straight line, and/or determining the starting and ending time of the matching segment of the first media object and the second media object according to the starting point and the ending point of the third matching straight line. By removing the part with low similarity at the beginning and the end of the matching straight line, keeping the middle section of the straight line with high similarity, and then determining the similarity condition of the first media object and the second media object, the comparison accuracy can be improved, and the start-stop time of the matching segment can be obtained more accurately.

The specific method for removing the part which does not reach the monomer similarity set value at the beginning/end of the matching straight line can be as follows: and checking from the starting point/the end point of the matched straight line to the middle in sequence to judge whether the monomer similarity set value is reached, and removing a plurality of points between the point and the starting point/the end point after finding the first point reaching the monomer similarity set value.

It should be noted that the monomer similarity setting value may be a specific numerical value of the monomer similarity, and it is determined whether a point reaches the numerical value during the inspection; or may be a proportional value, and it is determined whether or not a point reaches the proportional value when compared with the average value or the maximum value of all points included in the first matching straight line/the second matching straight line in the inspection.

Further, the similarity matrix may be obtained by comprehensively considering similarity of multiple media. Specifically, in the embodiment of the present disclosure, a plurality of types of first media feature sequences of a first media object and a plurality of types of second media feature sequences of a second media object obtained by using a plurality of extraction methods may be simultaneously obtained, and a similarity matrix may be determined according to the plurality of types of first media feature sequences and the plurality of types of second media feature sequences. Similarity between the two media objects is then determined using a similarity matrix based on the sequences of the multi-type media features.

Fig. 5 is a schematic flow chart diagram of determining a similarity matrix for media feature alignment based on multiple types of first media feature sequences and second media feature sequences according to an embodiment of the disclosure. Referring to fig. 5, a method for comparing media characteristics according to an embodiment of the disclosure specifically includes:

Step S51, obtaining multiple types of first media feature sequences of the first media object and multiple types of second media feature sequences of the second media object obtained by multiple extraction methods, where each type of first media feature sequence includes multiple first media feature monomers, and each type of second media feature sequence includes multiple second media feature monomers. For example, the floating-point number feature sequence and the binarization feature sequence of the first media object and the second media object are obtained simultaneously. Thereafter, the process proceeds to step S52.

Step S52, calculating the individual similarity between the first media feature individual and the second media feature individual of the same type for the multiple first media feature sequences and the multiple second media feature sequences, which may specifically determine the individual similarity by using the process shown in step S20 in the foregoing embodiment. Thus, the similarity of various monomers is obtained corresponding to various media characteristic sequences. Thereafter, the process proceeds to step S53.

Step S53, determining the average value of the similarity of the plurality of monomers, and determining the similarity matrix between the first media characteristic sequence and the second media characteristic sequence according to the average value of the similarity of the plurality of monomers; alternatively, the minimum value of the similarity of the plurality of monomers is determined, and the similarity matrix is determined according to the minimum value of the similarity of the plurality of monomers, and specifically, the similarity matrix may be determined by using the process shown in step S30 in the foregoing embodiment.

Thereafter, the process proceeds to step S40 of the foregoing example, and a similarity of the first media object and the second media object is determined using the similarity matrix based on the similarity of the plurality of types of singles in step S40.

The effect of determining the similarity matrix by using the average value or the minimum value of the multiple similarities is as follows: the media feature comparison using the similarity obtained from a single media feature (such as the similarity matrix and the linear similarity) may have a mismatching situation, and by taking the average value or the minimum value of the similarities of multiple media features, the mismatching problem can be reduced or eliminated, thereby improving the accuracy of the media feature comparison.

It should be noted that before taking the average value or the minimum value of the similarity of the multiple monomers, it is necessary to ensure that the similarity of the various monomers has a consistent value range, for example, the value ranges of the similarity of all types of monomers may be set to 0 to 1 in advance, and in fact, the value ranges of the similarity of the determined monomers are set to 0 to 1 in the foregoing examples of the similarity of the monomers determined according to the cosine distance and the examples of the similarity of the monomers determined according to the hamming distance.

Fig. 6 is a schematic structural diagram of an embodiment of the apparatus 100 for media feature comparison according to the present disclosure. Referring to fig. 6, an apparatus 100 for comparing media characteristics according to an example of the present disclosure mainly includes: the media feature sequence acquisition module 110, the individual similarity determination module 120, the similarity matrix determination module 130, and the similar situation determination module 140.

the media characteristic sequence acquiring module 110 is configured to acquire a media characteristic sequence of a first media object as a first media characteristic sequence, and acquire a media characteristic sequence of a second media object as a second media characteristic sequence. The first media object and the second media object are two media to be compared. Specifically, the first media feature sequence includes a plurality of first media feature monomers arranged in sequence, and the second media feature sequence includes a plurality of second media feature monomers arranged in sequence.

The individual similarity determination module 120 is configured to determine individual similarities between each of the first media feature individuals and each of the second media feature individuals. Each monomer similarity is used to indicate the degree of similarity between two media feature monomers, and specifically, the greater the monomer similarity, the more similar the media feature monomers.

In an embodiment of the disclosure, when the first media feature sequence and the second media feature sequence acquired by the media feature sequence acquiring module 110 are both floating-point features, the single similarity determining module 120 includes a sub-module, configured to determine the single similarity according to a cosine distance (alternatively referred to as a cosine similarity) between the first media feature single and the second media feature single.

In the embodiment of the disclosure, when the first media feature sequence and the second media feature sequence acquired by the media feature sequence acquiring module 110 are binary features at the same time, the single similarity determining module 120 includes a sub-module, configured to determine the single similarity according to a Hamming distance (Hamming distance) between the first media feature single and the second media feature single.

the similarity matrix determining module 130 is configured to determine a similarity matrix between the first media feature sequence and the second media feature sequence according to the individual similarity.

It should be noted that, in actual operation, the individual similarity determining module 120 and the similarity matrix determining module 130 are not necessarily independent, but the individual similarity determining module 120 may be a sub-module of the similarity matrix determining module 130, and the similarity matrix determining module 130 is configured to determine a similarity matrix and calculate the corresponding individual similarity in the process of determining each point of the similarity matrix.

the similarity determination module 140 is configured to determine a similarity between the first media object and the second media object according to the similarity matrix. Specifically, the similarity determination module 140 is configured to determine a similarity degree between the first media object and the second media object according to the similarity matrix, and may represent the similarity degree by using the comparison score, and/or determine start and end times of matching segments of the first media object and the second media object according to the similarity matrix.

in some embodiments of the present disclosure, the similarity determination module 140 includes a sub-module for determining the similarity of the first media object and the second media object based on the straight lines in the similarity matrix. Specifically, the sub-module is configured to: determining a straight line with the highest straight line similarity in the similarity matrix, wherein the straight line is not called a matching straight line; determining the straight line similarity of the matching straight lines as the similarity degree of the first media object and the second media object, and/or determining the matching segments of the first media object and the second media object according to a plurality of first media feature monomers and a plurality of second media feature monomers corresponding to the matching straight lines.

In an embodiment of the present disclosure, the similarity determination module 140 may include a dynamic programming comparison sub-module (not shown in the drawings) for determining the similarity between two media objects according to the similarity matrix by using a dynamic programming method. Fig. 7 is a schematic structural diagram of the similarity determination module 140 including each unit of the dynamic programming comparison submodule according to an embodiment of the present disclosure. Referring to fig. 7, in one embodiment, the similarity determination module 140 of the disclosed example includes:

The straight line similarity determining unit 141 is configured to determine the straight line similarity of each candidate straight line according to the individual similarity included in the candidate straight line. The alternative straight lines are a plurality of straight lines of which the slopes in the similarity matrix are preset slope set values. Specifically, the straight line similarity of a straight line may be set as an average value of the individual monomer similarities included in the straight line, or may be set as a total value of the individual monomer similarities included in the straight line.

It should be noted that, in an embodiment of the present disclosure, the straight line similarity determination unit 141 further includes a subunit, configured to exclude from the candidate straight lines those straight lines that include monomer similarities whose number is less than a preset straight line length setting value. Alternatively, the candidate straight lines used by the straight line similarity determination unit 141 also have to satisfy: the number of monomer similarities contained reaches a preset linear length set value.

A first matching straight line determining unit 142, configured to determine a candidate straight line with the largest similarity of the straight lines from the multiple candidate straight lines, and define the candidate straight line as a first matching straight line.

The first comparing unit 143 is configured to determine the straight line similarity of the first matching straight line as a comparison score, to represent the similarity between the first media object and the second media object, and/or to determine the start-stop time of the matching segment in the two media objects according to the start point and the end point of the first matching straight line.

In an embodiment of the present disclosure, the similarity determination module 140 may include a constant speed media comparison sub-module (not shown in the drawings) for determining the similarity between two media objects according to the similarity matrix by using a constant speed media method. Fig. 8 is a schematic structural diagram of the similarity determination module 140 including units of the constant velocity media comparison sub-module according to an embodiment of the present disclosure. Referring to fig. 8, in one embodiment, the similarity determination module 140 of the disclosed example includes:

And an extreme point determining unit 144, configured to select multiple points with the largest monomer similarity in the similarity matrix, and define the multiple points as similarity extreme points.

A second matching straight line determining unit 145, configured to fit a straight line in the similarity matrix as a second matching straight line based on the multiple extreme similarity points. In some examples, the second matching straight line determining unit 145 is specifically configured to fit a straight line having a preset slope setting value or close to the preset slope setting value as the second matching straight line based on the plurality of similarity extreme points. Specifically, the second matching straight line determining unit 145 may be configured to fit a straight line having a slope close to a slope setting value in the similarity matrix by using a random sample consensus method.

The second comparing unit 146 is configured to determine a comparison score according to a plurality of monomer similarities included in the second matching straight line (for example, an average value of the monomer similarities on the second matching straight line may be determined as the comparison score), so as to represent a similarity degree between the first media object and the second media object, and/or determine a start-stop time of a matching segment between the two media objects according to a start point and an end point of the second matching straight line.

In some embodiments of the present disclosure, the similar situation determining module 140 further comprises: a third matching straight line determining unit (not shown in the figure) is configured to detect a beginning portion and an ending portion of the first matching straight line or the second matching straight line, determine whether a point (monomer similarity) of the beginning portion and the ending portion of the first matching straight line/the second matching straight line reaches a preset monomer similarity set value, remove a portion of the beginning portion and the ending portion of the first matching straight line/the second matching straight line, which does not reach the monomer similarity set value (i.e., the monomer similarity is not high), and retain a middle straight line and define the middle straight line as a third matching straight line; and a third comparing unit (not shown in the figure) for determining the comparison score according to the line similarity of the third matching straight line, and determining the start-stop time of the matching segment according to the start point and the end point of the third matching straight line.

Further, the similarity matrix may be obtained by comprehensively considering similarity of multiple media. Fig. 9 is a block diagram of a media feature matching apparatus 100 for determining a similarity matrix based on a plurality of types of first media feature sequences and second media feature sequences according to an embodiment of the disclosure. Referring to fig. 9, a media feature comparison apparatus 100 according to an embodiment of the disclosure specifically includes:

the multi-type media feature sequence submodule 111 is configured to obtain, by using multiple extraction methods, multiple types of first media feature sequences of a first media object and multiple types of second media feature sequences of a second media object at the same time, where each type of first media feature sequence includes multiple first media feature monomers, and each type of second media feature sequence includes multiple second media feature monomers.

the multi-type monomer similarity determining submodule 121 is configured to calculate, for multiple first media feature sequences and multiple second media feature sequences, monomer similarities between first media feature monomers and second media feature monomers of the same type, respectively, and obtain multiple monomer similarities.

The similarity matrix determination submodule 131 is configured to determine an average value or a minimum value of the similarity of the plurality of single media, and determine a similarity matrix between the first media feature sequence and the second media feature sequence according to the average value or the minimum value of the similarity of the plurality of single media.

The similarity determination module 140 is specifically configured to determine the similarity between the first media object and the second media object by using the similarity matrix obtained based on the similarity between the plurality of types of monomers.

fig. 10 is a hardware block diagram illustrating a media feature comparison hardware apparatus according to an embodiment of the present disclosure. As shown in fig. 10, a media feature comparison hardware apparatus 200 according to an embodiment of the present disclosure includes a memory 201 and a processor 202. The components of the media feature comparison hardware device 200 are interconnected by a bus system and/or other form of connection mechanism (not shown).

The memory 201 is used to store non-transitory computer readable instructions. In particular, memory 201 may include one or more computer program products that may include various forms of computer-readable storage media, such as volatile memory and/or non-volatile memory. The volatile memory may include, for example, Random Access Memory (RAM), cache memory (cache), and/or the like. The non-volatile memory may include, for example, Read Only Memory (ROM), hard disk, flash memory, etc.

The processor 202 may be a Central Processing Unit (CPU) or other form of processing unit having data processing capabilities and/or instruction execution capabilities, and may control the media features versus other components in the hardware device 200 to perform desired functions. In an embodiment of the present disclosure, the processor 202 is configured to execute the computer readable instructions stored in the memory 201, so that the media feature matching hardware device 200 performs all or part of the aforementioned steps of the matching method of media features according to the embodiments of the present disclosure.

Fig. 11 is a schematic diagram illustrating a computer-readable storage medium according to an embodiment of the present disclosure. As shown in fig. 11, a computer-readable storage medium 300 having non-transitory computer-readable instructions 301 stored thereon according to an embodiment of the present disclosure. When the non-transitory computer readable instructions 301 are executed by a processor, all or part of the steps of the method for matching media characteristics according to the embodiments of the present disclosure are performed.

Fig. 12 is a diagram illustrating a hardware structure of a terminal device according to an embodiment of the present disclosure. The terminal device may be implemented in various forms, and the terminal device in the present disclosure may include, but is not limited to, mobile terminal devices such as a mobile phone, a smart phone, a notebook computer, a digital broadcast receiver, a PDA (personal digital assistant), a PAD (tablet computer), a PMP (portable multimedia player), a navigation apparatus, a vehicle-mounted terminal device, a vehicle-mounted display terminal, a vehicle-mounted electronic rear view mirror, and the like, and fixed terminal devices such as a digital TV, a desktop computer, and the like.

As shown in fig. 12, the terminal device 1100 may include a wireless communication unit 1110, an a/V (audio/video) input unit 1120, a user input unit 1130, a sensing unit 1140, an output unit 1150, a memory 1160, an interface unit 1170, a controller 1180, a power supply unit 1190, and the like. Fig. 12 shows a terminal device having various components, but it is to be understood that not all of the illustrated components are required to be implemented. More or fewer components may alternatively be implemented.

The wireless communication unit 1110 allows, among other things, radio communication between the terminal device 1100 and a wireless communication system or network. The a/V input unit 1120 is for receiving an audio or video signal. The user input unit 1130 may generate key input data to control various operations of the terminal device according to a command input by a user. The sensing unit 1140 detects the current state of the terminal device 1100, the position of the terminal device 1100, the presence or absence of a touch input by a user to the terminal device 1100, the orientation of the terminal device 1100, acceleration or deceleration movement and direction of the terminal device 1100, and the like, and generates a command or signal for controlling the operation of the terminal device 1100. The interface unit 1170 serves as an interface through which at least one external device is connected to the terminal apparatus 1100. The output unit 1150 is configured to provide output signals in a visual, audio, and/or tactile manner. The memory 1160 may store software programs and the like for processing and controlling operations performed by the controller 1180, or may temporarily store data that has been output or is to be output. Memory 1160 may include at least one type of storage media. Also, the terminal apparatus 1100 may cooperate with a network storage device that performs a storage function of the memory 1160 through a network connection. The controller 1180 generally controls the overall operation of the terminal device. In addition, the controller 1180 may include a multimedia module for reproducing or playing back multimedia data. The controller 1180 may perform a pattern recognition process to recognize a handwriting input or a picture drawing input performed on the touch screen as a character or an image. The power supply unit 1190 receives external power or internal power and provides appropriate power required to operate the various elements and components under the control of the controller 1180.

Various embodiments of the methods of alignment of media features presented in this disclosure may be implemented using a computer-readable medium, such as computer software, hardware, or any combination thereof. For a hardware implementation, various embodiments of the method for alignment of media features presented in this disclosure may be implemented using at least one of an Application Specific Integrated Circuit (ASIC), a Digital Signal Processor (DSP), a Digital Signal Processing Device (DSPD), a Programmable Logic Device (PLD), a Field Programmable Gate Array (FPGA), a processor, a controller, a microcontroller, a microprocessor, an electronic unit designed to perform the functions described herein, and in some cases, various embodiments of the method for alignment of media features presented in this disclosure may be implemented in the controller 1180. For software implementation, various embodiments of the media feature comparison method presented in the present disclosure may be implemented with a separate software module that allows at least one function or operation to be performed. The software codes may be implemented by software applications (or programs) written in any suitable programming language, which may be stored in memory 1160 and executed by controller 1180.

In the above, according to the media feature comparison method, device, hardware device, computer-readable storage medium and terminal device in the embodiments of the present disclosure, the similarity between the media objects is determined based on the similarity matrix between the two media objects, so that the efficiency and accuracy of media comparison can be improved. Furthermore, the similarity degree and/or the matching segment of the two media objects are determined according to the straight line in the similarity matrix, so that the efficiency and the accuracy of media comparison can be greatly improved; in addition, the accuracy of media comparison can be greatly improved by comparing the media characteristics based on various types of media characteristic sequences.

the foregoing describes the general principles of the present disclosure in conjunction with specific embodiments, however, it is noted that the advantages, effects, etc. mentioned in the present disclosure are merely examples and are not limiting, and they should not be considered essential to the various embodiments of the present disclosure. Furthermore, the foregoing disclosure of specific details is for the purpose of illustration and description and is not intended to be limiting, since the disclosure is not intended to be limited to the specific details so described.

The block diagrams of devices, apparatuses, systems referred to in this disclosure are only given as illustrative examples and are not intended to require or imply that the connections, arrangements, configurations, etc. must be made in the manner shown in the block diagrams. These devices, apparatuses, devices, systems may be connected, arranged, configured in any manner, as will be appreciated by those skilled in the art. Words such as "including," "comprising," "having," and the like are open-ended words that mean "including, but not limited to," and are used interchangeably therewith. The words "or" and "as used herein mean, and are used interchangeably with, the word" and/or, "unless the context clearly dictates otherwise. The word "such as" is used herein to mean, and is used interchangeably with, the phrase "such as but not limited to".

Also, as used herein, "or" as used in a list of items beginning with "at least one" indicates a separate list, such that, for example, a list of "A, B or at least one of C" means A or B or C, or AB or AC or BC, or ABC (i.e., A and B and C). Furthermore, the word "exemplary" does not mean that the described example is preferred or better than other examples.

It is also noted that in the systems and methods of the present disclosure, components or steps may be decomposed and/or re-combined. These decompositions and/or recombinations are to be considered equivalents of the present disclosure.

Various changes, substitutions and alterations to the techniques described herein may be made without departing from the techniques of the teachings as defined by the appended claims. Moreover, the scope of the claims of the present disclosure is not limited to the particular aspects of the process, machine, manufacture, composition of matter, means, methods and acts described above. Processes, machines, manufacture, compositions of matter, means, methods, or acts, presently existing or later to be developed that perform substantially the same function or achieve substantially the same result as the corresponding aspects described herein may be utilized. Accordingly, the appended claims are intended to include within their scope such processes, machines, manufacture, compositions of matter, means, methods, or acts.

The previous description of the disclosed aspects is provided to enable any person skilled in the art to make or use the present disclosure. Various modifications to these aspects will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other aspects without departing from the scope of the disclosure. Thus, the present disclosure is not intended to be limited to the aspects shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

The foregoing description has been presented for purposes of illustration and description. Furthermore, this description is not intended to limit embodiments of the disclosure to the form disclosed herein. While a number of example aspects and embodiments have been discussed above, those of skill in the art will recognize certain variations, modifications, alterations, additions and sub-combinations thereof.