System for Identifying Motion Video Content

• US 20100166250A1
• Filed: 05/22/2008
• Published: 07/01/2010
• Est. Priority Date: 08/27/2007
• Status: Active Grant

• Current Assignee: ZTE Corporation
• Original Assignee: Yuvad Technologies Co. Ltd
• Inventors: Zhang, Ji
• Granted Patent: US 8,452,043 B2
• Time in Patent Office: Days
• US Class Current: 382/100
• CPC Class Codes: G06F 16/70 of video data
• CPC Class Codes: G06V 20/48 Matching video sequences
• CPC Class Codes: H04N 5/144 Movement detection for video coding H04N19/503; analysis of motion in general G06T7/20

Abstract

A system for identifying motion video content, with a registered fmgerprint databse in advance for video contents of broadcasting video signals, wherein said system at least comprises a frame buffer into which a consecutive of video frame images of a motion video content to be identified are stored; a frame sampler by which sample values on the video frame images are obtained; a fingerprint store in which the sample values are held as a fingerprint A for search in the fingerprint database; and a matcher which performs a fingerprint pattern matching algorithm between the fingerprint A for search in the fingerprint database and fingerprints B contained in the fingerprint database so as to determine whether the motion video content has ever been broadcasted before. The system according to the present invention can effectively organize, archive, and search video content; lower the cost of digital storage devices; and identify video content efficiently and with minimal or no human interactions.

Claims

1. A system for identifying motion video content, with a registered fingerprint database in advance for video contents of broadcasting video signals, wherein said system at least comprises

a frame buffer into which a consecutive of video frame images of a motion video content to be identified are stored;

a frame sampler by which sample values on the video frame images are obtained;

a fingerprint store in which the sample values are held as a fingerprint A for search in the fingerprint database; and

a matcher which performs a fingerprint pattern matching algorithm between the fingerprint A for search in the fingerprint database and fringerprints B contained in the fingerprint database so as to determine whether the motion video content has ever been broadcasted before.

2. The system of claim 1, wherein in the fingerprint A for search in the fmgerprint database and fringerprints B contained in the fingerprint database, samples in the corresponding image positions are used to obtain sum of absolute values (SAD);

the series of sum of absolute differences (SSAD) is obtained by adding all of the SAD values for all aligned frames between the fingerprint A for search in the fingerprint database and fringerprints B contained in the fingerprint database.

3. The system of claim 2, wherein the SSAD values, denoted as S(1), S(2), . . . , S(n), S(n+1), are stored in a pattern array store, a pattern extractor inspects all neighboring SSAD values and obtains the pattern values, denoted as P(1), P(2), P(3), and so forth,

P(n)=(S(n)−

S(n−

1))/S(n)

where S(n) represents the difference between the fingerprint A and fingerprint B on their respective n-th frame within the fingerprint window, the index n refers to a different video frame each time the fingerprint array B is shifted by one frame relative to fingerprint A; and

where P(1) is not defined and will not be used, it does the above only if S(n) is not zero and a fixed threshold, otherwise, P(n) is set to zero,

the extracted pattern values form another series of numbers which are then stored in a pattern store, a pattern inspector selects the values contained in pattern store by the following steps;

selecting a specific position, say m, within the pattern store and identify all of the values within a window of size 2M-1 of position m;

P(m−

M+1), P(m−

M+2), . . . , P(m−

1), P(m), P(m+1), . . . , P(m+M−

2), P(m+M−

1),

these values are then added together by a pattern value collector and yields a result C(m), in the following way;

C(m)=−

P(m−

M+1)−

. . .−

P(m−

1)−

P(m)+P(m+1)+. . .+P(m+M−

1)

where M is a constant which is chosen so that there are sufficient number of values of P to be included in the calculation of C within the sliding window of 2M−

1,

finally, the value C(m) is compared with a user given threshold to determine if a match has been found between the fingerprint A and possible fingerprint B, and

the frame number is determined through the above process and output to histogram collector.

4. The system of claim 3, wherein the histogram collector gathers all of the pattern values C(m) that have exceeded the given threshold, count the number of times each value exceeds the threshold, and store them into an array, each item in the array holds the value m, C(m) and the number of times that C(m) has crossed the threshold.

5. The system of claim 4, wherein a maximum value selector inspects all such values within the histogram for the value that has appeared the most number of times, this value refers to the frame that is identified as the fingerprint matched frame.

6. The system of claim 1, wherein the sample values are selected for luminance or brightness of the sampled video image.

7. The system of claim 1, wherein the samples are made on the same positions within each video frame, and same number of video samples are made in each frame and their positions within each frame are fixed from frame to frame.

8. The system of claim 1, wherein the samples are made on the image so that they are as evenly spread over the image as possible.

9. The system of claim 1, wherein the samples are at an integer fraction positions of the video image resolution at both the horizontal and vertical directions.

10. The system of claim 1, wherein there are 5 samples within each frame, in which

the sample 1 is in the middle position of the image;

the sample 2 is in the middle in horizontal direction and at top quarter of vertical image size;

the sample 3 is in the middle in horizontal direction and at bottom quarter of vertical image size;

the sample 4 is in the middle in vertical direction and at left quarter of horizontal image size; and

the sample 5 is in the middle in vertical direction and at right quarter of horizontal image size.