OPTIMIZING VIDEO STREAM PROCESSING

• US 20110188701A1
• Filed: 02/01/2010
• Published: 08/04/2011
• Est. Priority Date: 02/01/2010
• Status: Active Grant

• Current Assignee: Kyndryl Incorporated
• Original Assignee: International Business Machines Corporation
• Inventors: Zhai, Yun, Bobbitt, Russell Patrick, Miyazawa, Sachiko, Pankanti, Sharathchandra Umapathirao, Fan, Quanfu
• Granted Patent: US 8,259,175 B2
• Time in Patent Office: Days
• US Class Current: 382/100
• CPC Class Codes: G06Q 20/202 Interconnection or interaction of plural electronic cash registers [ECR] or to host computer, e.g. network details, transfer of information from host to ECR or from ECR to ECR
• CPC Class Codes: G06V 10/96 Management of image or video recognition tasks
• CPC Class Codes: G06V 20/52 Surveillance or monitoring of activities, e.g. for recognising suspicious objects recognising microscopic objects G06V20/69
• CPC Class Codes: H04N 7/181 for receiving images from a plurality of remote sources
• CPC Class Codes: H04N 7/188 Capturing isolated or intermittent images triggered by the occurrence of a predetermined event, e.g. an object reaching a predetermined position signal generation from motion picture films H04N5/253

Abstract

The present invention involves implementation of an intelligent switching program, whereby the processing power required to monitor check-out stations is considerably reduced. The present invention monitors a subset of check-out stations at any given time, instead of monitoring all check-out stations at all times. The subset of check-out stations is determined dynamically according to, but not limited to, cashier records, input parameters from the user, current lane activity, past lane activity, time of day, etc. Statistical models (e.g., effective population sampling and/or population hypothesis tests) are developed along these lines that guide the lane selection process, whereby increases in the false-negative rate due to failure to monitor particular lanes when events of interest occur are controlled. By monitoring fewer check-out stations, while maintaining target performance accuracy, the amount of data that end users must deal with is significantly reduced.

Claims

1. A method implemented in a computer infrastructure having computer executable code tangibly embodied on a computer readable storage medium having programming instructions, the method comprises:

obtaining streams of video and transaction data from one or more hardware devices;

combining the streams of video and transaction data into individual transaction units;

determining processing priority for each transaction unit of the individual transaction units; and

processing a fraction of the individual transaction units based on the priority for each transaction unit.

2. The method of claim 1, wherein the determining processing priority for each transaction unit comprises applying a set of rules.

3. The method of claim 2, wherein the set of rules are dynamically updated by transaction data.

4. The method of claim 1, wherein the determining processing priority for each transaction unit comprises using one or more statistical models to determine correlations between features of the transaction unit.

5. The method of claim 4, wherein one or more statistical models comprises Gaussian, Poisson, exponential, uniform or other statistical models.

6. The method of claim 1, further comprises detecting an irregular activity committed by a cashier.

7. The method of claim 6, further comprises placing the transactions units in a transaction priority queue in an order of relative priority.

8. The method of claim 7, further comprises moving processed transaction units from the transaction priority queue to an archival queue after processing.

9. The method of claim 8, further comprises moving unprocessed transaction units from the transaction priority queue to the archival queue at regular intervals.

10. The method of claim 9, further comprises archiving the transaction units in the archival queue, and placing the transaction units in the archival queue in a persistent storage after archiving.

11. A computer program product comprising a computer readable storage medium having computer readable program code embodied in the storage medium, the computer program product includes at least one module operable to:

obtain streams of video and transaction data from one or more hardware device;

combine the streams of video and transaction data into individual transaction units;

determine processing priority for each transaction unit of the individual transaction units; and

process a fraction of the individual transaction units based on the priority for each transaction unit.

12. The computer program product of claim 11, wherein the computer readable program code for determining processing priority for each transaction unit comprises applying a set of rules.

13. The computer program product of claim 12, wherein the set of rules are dynamically updated by transaction data.

14. The computer program product of claim 11, wherein the computer readable program code for determining processing priority for each transaction unit comprises using one or more statistical model to determine correlations between features of the transaction unit.

15. The computer program product of claim 14, wherein one or more statistical model comprises Gaussian, Poisson, exponential, uniform or other statistical models.

16. The computer program product of claim 11, further includes at least one module operable to:

detect an irregular activity committed by a cashier;

place the transaction units in a transaction priority queue in an order of relative priority;

move processed transaction units from the transaction priority queue to an archival queue after processing;

move unprocessed transaction units from the transaction priority queue to the archival queue at regular interval;

archive the transaction units in the archival queue; and

place the transaction units in the archival queue in a persistent storage after archiving.

17. A system for processing video, comprising

a memory;

and

at least one processor coupled to said memory and operative to;

obtain streams of video and transaction data from one or more hardware device;

combine the streams of video and transaction data into individual transaction units;

determine processing priority for each transaction unit of the individual transaction units; and

process a fraction of the individual transaction units based on the priority for each transaction unit.

18. The system of claim 17, wherein for determining processing priority for each transaction unit comprises applying a set of rules.

19. The system of claim 18, wherein the set of rules are dynamically updated by transaction data.

20. The system of claim 17, wherein for determining processing priority for each transaction unit comprises using one or more statistical model to determine correlations between features of the transaction unit.

21. The system of claim 17, wherein the at least one processor coupled to said memory is further operative to detect an irregular activity committed by a cashier.

22. The system of claim 21, wherein the at least one processor coupled to said memory is further operative to place the transactions units in a transaction priority queue in an order of relative priority.

23. The system of claim 22, wherein the at least one processor coupled to said memory is further operative to move processed transaction units from the transaction priority queue to an archival queue after processing;

and move unprocessed transaction units from the transaction priority queue to the archival queue at regular interval;

24. The system of claim 23, wherein the at least one processor coupled to said memory is further operative to archive the transaction units in the archival queue;

and place the transaction units in the archival queue in a persistent storage after archiving.

25. A computer system for processing video, the system comprising:

a CPU, a computer readable memory and a computer readable storage media;

first program instructions to obtain streams of video and transaction data from one or more hardware device;

second program instructions to combine the streams of video and transaction data into individual transaction units;

third program instructions to determine processing priority for each transaction unit of the individual transaction units; and

fourth program instructions to process a fraction of the individual transaction units based on the priority for each transaction unit

wherein the first, second, third and fourth program instructions are stored on the computer readable storage media for execution by the CPU via the computer readable memory.