IP Library Granted Patent US 9,363,467
Granted Patent B2
US 9,363,467 · App. 14/093,399 · Granted Jun 7, 2016

Environmental signatures for forensic analysis and alignment of media recordings

Inventors: Ravi Garg (College Park, MD); Avinash L. Varna (Chandler, AZ); Adi Hajj-Ahmad (College Park, MD); Min Wu (Clarksville, MD)
Assignee: University of Maryland, College Park
H04N5/913H04N2005/91342
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Quick Facts
Patent No.
US 9,363,467
App. No.
14/093,399
Granted
Jun 7, 2016
Kind
B2
Abstract

Various systems and methods may benefit from determination of environmental signatures in recordings. For example, such signatures may aid forensic analysis and alignment of media recordings, such as alignment of audio or video recordings. A method can include reading data representative of sensed light in a visual track of a video recording. The method can also include extracting an electric network frequency signal from the data representative of sensed light.

Claims (29)

1. A method, comprising:

reading data representative of sensed light in a visual track of a video recording; and

extracting an electric network frequency signal from the data representative of sensed light, wherein the extracting the electric network frequency signal comprises performing a row by row analysis of the data representative of sensed light; and applying the extracted electric network frequency signal to perform at least one task of authentication of the video recording or data analytics of the video recording.

2. The method of claim 1 , wherein the extracting comprises performing an aliasing analysis.

3. The method of claim 2 , wherein the extracting additionally comprises supplying the filtered electric network frequency signal to a band-pass filter with a narrow passband.

4. The method of claim 1 , further comprising: determining a location of the sensed light based on the extracted electric network frequency signal.

5. The method of claim 1 , further comprising: determining whether tampering of the video recording has occurred by comparing the electric network frequency signal to another sample of electric network frequency signal.

6. A method, comprising:

reading data representative of sensed light in a visual track of a video recording;

extracting an electric network frequency signal from the data representative of sensed light synchronizing a plurality of multimedia streams based on the extracted electric network frequency signal; and outputting a time alignment information, location relationship, or both a time alignment and a location relationship of the multimedia streams based on the synchronizing.

7. A method, comprising:

reading an electric network frequency signal; and obtaining a location signature for the electric network frequency signal, wherein the location signature is on a smaller scale than a grid, and wherein the obtaining the location signature comprises passing the electric network frequency signal through one filter or a combination of filters and

subtracting an output of the one filter or the combination of filters from the electric network frequency signal; and applying the obtained location signature to perform at least one task of authentication of the video recording or data analytics of the video recording.

8. The method of claim 7 , further comprising: obtaining a location corresponding to the electric network frequency signal by comparing the location signature to at least one other location signature having a known location within a grid.

9. A method, comprising: reading an electric network frequency signal from a recording; determining a plurality of statistical characteristics of the electric network frequency signal; determining a location of the recording based on the plurality of statistical characteristics; and applying the determined location of the recording to perform at least one task of authentication of the video recording or data analytics of the video recording.

10. The method of claim 9 , wherein the plurality of statistical characteristics comprise at least two of a mean of the electric network frequency signal, a variance of the electric network frequency signal, and a dynamic range of the electric network frequency signal.

11. The method of claim 9 , wherein the determining the plurality of statistical characteristics comprises applying a transformation to a segment of the electric network frequency signal and examine statistical properties of the transformation.

12. An apparatus, comprising: at least one processor; and at least

one memory including computer program code,

wherein the at least one memory and the computer program code are configured to, with the at least one processor, cause the apparatus at least to

read data representative of sensed light in a visual track of a video recording; and

extract an electric network frequency signal from the data representative of sensed light,

wherein the extraction comprises performing a row by row analysis of the data representative of sensed light; and apply the extracted electric network frequency signal to perform at least one task of authentication of the video recording or data analytics of the video recording.

13. The apparatus of claim 12 , wherein the at least one memory and the computer program code are configured to, with the at least one processor, cause the apparatus at least to extract the electric network frequency signal by performing an aliasing analysis.

14. The apparatus of claim 13 , wherein the at least one memory and the computer program code are configured to, with the at least one processor, cause the apparatus at least to extract the electric network frequency by supplying the filtered electric network frequency signal to a band-pass filter with a narrow passband.

15. An apparatus, comprising: at least one processor; and at least one memory including computer program code, wherein the at least one memory and the computer program code are configured to, with the at least one processor, cause the apparatus at least to read an electric network frequency signal; and obtain a location signature for the electric network frequency signal by passing the electric network frequency signal through one filter or a combination of filters and subtracting an output of the one filter or the combination of filters from the electric network frequency signal, wherein the location signature is on a smaller scale than a grid; and apply the obtained location signature to perform at least one task of authentication of the video recording or data analytics of the video recording.

16. The apparatus of claim 15 , wherein the at least one memory and the computer program code are configured to, with the at least one processor, cause the apparatus at least to obtain a location corresponding to the electric network frequency signal by comparing the location signature to at least one other location signature having a known location within a grid.

17. An apparatus, comprising: at least one processor; and at least one memory including computer program code, wherein the at least one memory and the computer program code are configured to, with the at least one processor, cause the apparatus at least to read an electric network frequency signal from a recording; determine a plurality of statistical characteristics of the electric network frequency signal; and determine a location of the recording based on the plurality of statistical characteristics; and apply the determined location of the recording to perform at least one task of authentication of the video recording or data analytics of the video recording.

18. The apparatus of claim 17 , wherein the at least one memory and the computer program code are configured to, with the at least one processor, cause the apparatus at least to determine the plurality of statistical characteristics by applying a transformation to a segment of the electric network frequency signal and examine statistical properties of the transformation.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 19, 2015
From: GARG, RAVI; VARNA, AVINASH; WU, MIN; HAJJ-AHMAD, ADI
To: UNIVERSITY OF MARYLAND, COLLEGE PARK
Reel/Frame 037093/0001 →
Continuity (2)
Provisional Application 61731353 · Nov 29, 2012
Related Publication 20140147097A1 · May 29, 2014