IP Library Granted Patent US 7,925,536
Granted Patent B2
US 7,925,536 · App. 11/802,895 · Granted Apr 12, 2011

Intelligent video verification of point of sale (POS) transactions

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Quick Facts
Patent No.
US 7,925,536
App. No.
11/802,895
Granted
Apr 12, 2011
Kind
B2
Abstract

Non video data regarding a point of sale (POS) transaction is received. POS primitives are generated based on the received non video POS data. Video data regarding a corresponding POS transaction is received. Video primitives are generated based on the received video data. An exceptional transaction is inferred based on a corresponding exceptional transaction rule and at least one of the generated POS primitives or video primitives.

Claims (75)

1. A non-transitory computer-readable medium comprising software for monitoring a point of sale (POS) transaction, which software, when executed by a computer system, causes the computer system to perform operations comprising a method of:

receiving non video data regarding the point of sale (POS) transaction;

processing the received non video POS data to generate POS primitives, the POS primitives being data descriptions of the content of the received non video POS data;

receiving video data regarding the corresponding POS transaction;

processing the received video data to generate video primitives, the video primitives being data descriptions of the content of the received video data;

defining exceptional transaction rules based on at least one predetermined video data event and at least one predetermined non video data event; and

inferring an exceptional transaction based on a corresponding exceptional transaction rule and at least one of the generated POS primitives or video primitives.

2. The medium as set forth in claim 1 , wherein the method further includes:

defining policy violation rules based at least on predetermined exceptional transactions; and

determining a policy violation based on a corresponding policy violation rule and the inferred exceptional transaction.

3. The medium as set forth in claim 2 , wherein the method further includes:

generating a policy violation report based on the determined policy violation.

4. The medium as set forth in claim 1 , wherein the method further includes:

generating an exceptional transaction report based on the inferred exceptional transaction.

5. The medium as set forth in claim 1 , wherein the POS primitives and video primitives are generated contemporaneously.

6. The medium as set forth in claim 1 , wherein the method further includes:

storing the video and POS primitives in a primitive database prior to the step of inferring; and

one of performing the step of inferring in real time or withdrawing the video and POS primitives from the primitive database and inferring the exceptional transaction based on the withdrawn video and POS primitives.

7. The medium as set forth in claim 1 , wherein receiving video data includes:

receiving video data from a first video camera.

8. The medium as set forth in claim 7 , wherein receiving video data further includes:

receiving auxiliary video data from one or more auxiliary video cameras.

9. The medium as set forth in claim 1 , wherein the method is performed locally.

10. The medium as set forth in claim 1 , wherein the method further includes:

receiving the non video data regarding the POS transaction via a communication channel at a remote location;

receiving the video data regarding the corresponding POS transaction via the communication channel at the remote location;

processing the received non video POS data to generate POS primitives at the remote location;

processing the received video data to generate video primitives at the remote location;

defining exceptional transactions rules based on at least one predetermined non video data event and at least one predetermined video data event at the remote location; and

inferring the exceptional transaction at the remote location.

11. A method for monitoring a point of sale (POS) transaction, comprising:

receiving non video data regarding the point of sale (POS) transaction;

processing the received non video POS data to generate POS primitives using a first computer processor, the POS primitives being data descriptions of the content of the received non video POS data;

receiving video data regarding the corresponding POS transaction;

processing the received video data to generate video primitives using the first or a second a computer processor, the video primitives being data descriptions of the content of the received video data;

defining exceptional transaction rules based on at least one predetermined video data event and at least one predetermined non video data event; and

inferring an exceptional transaction based on a corresponding exceptional transaction rule and at least one of the generated POS primitives or video primitives.

12. A system, comprising:

a POS data parsing engine to receive non video data regarding a POS transaction and generate POS primitives, the POS primitives being data descriptions of the content of the received non video POS data;

a video content analysis engine to receive the video data regarding the corresponding POS transaction and generate video primitives, the video primitives being data descriptions of the content of the received video data;

an exceptional transaction inference engine to infer an exceptional transaction based on a corresponding exceptional transaction rule and at least on one of the generated POS primitives or video primitives; and

at least one computer processor to implement the POS data parsing engine, the video content analysis engine, and the exceptional transaction inference engine.

13. The medium as set forth in claim 1 , wherein the step of inferring further includes:

inferring an exceptional transaction based on a corresponding exceptional transaction rule, the generated POS primitives, and the generated video primitives.

14. The method as set forth in claim 11 , wherein the step of inferring further includes:

inferring an exceptional transaction based on a corresponding exceptional transaction rule, the generated POS primitives, and the generated video primitives.

15. The system as set forth in claim 12 , wherein the exception transaction inference engine infers an exceptional transaction based on a corresponding exceptional transaction rule, the generated POS primitives, and the generated video primitives.

16. A non-transitory computer-readable medium comprising software for monitoring a point of sale (POS) transaction, which software, when executed by a computer system, causes the computer system to perform operations comprising a method of:

receiving non video data regarding the point of sale (POS) transaction;

receiving video data regarding the corresponding POS transaction;

processing the received video data to generate video primitives, the video primitives being data descriptions of the content of the received video data;

defining exceptional transaction rules based on at least one predetermined video data event and at least one predetermined non video data event; and

inferring an exceptional transaction based on a corresponding exceptional transaction rule and at least one of the generated video primitives or the non video data.

17. The medium as set forth in claim 16 , wherein the step of inferring further includes:

inferring an exceptional transaction based on a corresponding exceptional transaction rule, the generated video primitives, and the non video data.

18. A method for monitoring a point of sale (POS) transaction, comprising:

receiving non video data regarding the point of sale (POS) transaction;

receiving video data regarding the corresponding POS transaction;

processing the received video data to generate video primitives using the first or a second a computer processor, the video primitives being data descriptions of the content of the received video data;

defining exceptional transaction rules based on at least one predetermined video data event and at least one predetermined non video data event; and

inferring an exceptional transaction based on a corresponding exceptional transaction rule and at least one of the generated video primitives or non video data.

19. The method as set forth in claim 18 , wherein the step of inferring further includes:

inferring an exceptional transaction based on a corresponding exceptional transaction rule, the generated video primitives, and the non video data.

20. A system, comprising:

a POS data parsing engine to receive non video data regarding a POS transaction;

a video content analysis engine to receive the video data regarding the corresponding POS transaction and generate video primitives, the video primitives being data descriptions of the content of the received video data;

an exceptional transaction inference engine to infer an exceptional transaction based on a corresponding exceptional transaction rule and at least on one of the generated video primitives or the non video data; and

at least one computer processor to implement the POS data parsing engine, the video content analysis engine, and the exceptional transaction inference engine.

21. The system as set forth in claim 20 , wherein the exception transaction inference engine infers an exceptional transaction based on a corresponding exceptional transaction rule, the generated video primitives, and the non video data.

22. A non-transitory computer-readable medium comprising software for monitoring a point of sale (POS) transaction, which software, when executed by a computer system, causes the computer system to perform operations comprising a method of:

receiving non video data regarding the point of sale (POS) transaction;

receiving video data regarding the corresponding POS transaction;

processing the received video data to generate processed video data;

defining exceptional transaction rules based on at least one predetermined video data event and at least one predetermined non video data event; and

inferring an exceptional transaction based on a corresponding exceptional transaction rule and at least one of the processed video data or the non video data.

Assignments (8)
NUNC PRO TUNC ASSIGNMENT Recorded Oct 23, 2022
From: AVIGILON FORTRESS CORPORATION
To: MOTOROLA SOLUTIONS, INC.
Reel/Frame 061746/0897 →
RELEASE OF SECURITY INTEREST Recorded Aug 21, 2018
From: HSBC BANK CANADA
To: AVIGILON FORTRESS CORPORATION
Reel/Frame 047032/0063 →
SECURITY INTEREST Recorded Apr 8, 2015
From: AVIGILON FORTRESS CORPORATION
To: HSBC BANK CANADA
Reel/Frame 035387/0569 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Dec 18, 2014
From: OBJECTVIDEO, INC.
To: AVIGILON FORTRESS CORPORATION
Reel/Frame 034552/0334 →
RELEASE OF SECURITY AGREEMENT/INTEREST Recorded Feb 24, 2012
From: RJF OV, LLC
To: OBJECTVIDEO, INC.
Reel/Frame 027810/0117 →
GRANT OF SECURITY INTEREST IN PATENT RIGHTS Recorded Oct 28, 2008
From: OBJECTVIDEO, INC.
To: RJF OV, LLC
Reel/Frame 021744/0464 →
SECURITY AGREEMENT Recorded Feb 8, 2008
From: OBJECTVIDEO, INC.
To: RJF OV, LLC
Reel/Frame 020478/0711 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jul 11, 2007
From: LIPTON, ALAN J.; VENETIANER, PETER L.; YU, LI; HU, YONGTONG; SCANLON, W. ANDREW; ZHANG, ZHONG; YIN, WEIHONG
To: OBJECTVIDEO, INC.
Reel/Frame 019579/0832 →