Vision-based method and apparatus for detecting fraudulent events in a retail environment

• US 20030040925A1
• Filed: 08/22/2001
• Published: 02/27/2003
• Est. Priority Date: 08/22/2001
• Status: Abandoned Application

• Current Assignee: Koninklijke Philips Electronics N.V. (Koninklijke Philips N.V.)
• Original Assignee: Koninklijke Philips Electronics N.V. (Koninklijke Philips N.V.)
• Inventors: Trajkovic, Miroslav, Gutta, Srinivas, Colmenarez, Antonio
• Application Number:
  US09/938,148
• Publication Number:
  US 20030040925A1
• Time in Patent Office: Days
• US Class Current: 705/1
• CPC Class Codes: G08B 13/19602 Image analysis to detect motion of the intruder, e.g. by frame subtraction
• CPC Class Codes: G08B 13/19615 wherein said pattern is defined by the user
• CPC Class Codes: G08B 13/19641 Multiple cameras having overlapping views on a single scene
• CPC Class Codes: G08B 13/19671 Addition of non-video data, i.e. metadata, to video stream
• CPC Class Codes: G08B 31/00 Predictive alarm systems characterised by extrapolation or other computation using updated historic data

Abstract

A method and apparatus are disclosed for monitoring a retail location using vision-based technologies to recognize predefined fraudulent events. Captured images are processed to identify one or more predefined fraudulent events and to initiate an appropriate response, such as sending notice to an employee for further investigation or recording the event for evidentiary purposes. A number of rules define various fraudulent events. For example, rules can be devised to detect when a patron is wearing stolen clothing out of the changing room, or when a patron is fraudulently attempting to return merchandise without a receipt. Each rule contains one or more conditions that must be satisfied and a corresponding action-item that should be performed when the rule is satisfied. At least one of the conditions for each rule identifies a feature that must be detected in an image using vision-based techniques. An event monitoring process is also disclosed that analyzes the captured images to detect one or more fraudulent events defined by the event rules.

Claims

1. A method for detecting a fraudulent event in a retail location, comprising:

establishing a rule defining said fraudulent event, said rule including at least one condition;

processing at least one image of said retail location to identify said condition; and

performing a defined action if said rule is satisfied.

2. The method of claim 1, further comprising the step of recording said at least one image if said rule is satisfied.

3. The method of claim 1, wherein said fraudulent event is a person stealing an item.

4. The method of claim 1, wherein said fraudulent event is a person attempting to return an item without a receipt.

5. The method of claim 4, wherein said person attempting to return an item without a receipt has not previously been detected in said retail location.

6. The method of claim 4, wherein said person attempting to return an item without a receipt has been detected in an area of said retail location where said item is stocked.

7. The method of claim 4, wherein said person attempting to return an item without a receipt was not carrying said item when said person entered said retail location.

8. The method of claim 1, wherein said processing step further comprises the step of performing a face recognition analysis on said image.

9. The method of claim 1, wherein said processing step further comprises the step of performing a feature extraction analysis on said image.

10. A method for detecting a fraudulent event at a retail location, comprising:

obtaining at least one image of said retail location;

analyzing said image using video content analysis techniques to identify at least one predefined feature in said image associated with said fraudulent event; and

performing a defined action if said rule is satisfied.

11. The method of claim 10, wherein said fraudulent event is a person stealing an item.

12. The method of claim 10, wherein said fraudulent event is a person attempting to return an item without a receipt.

13. A system for detecting a fraudulent event in a retail location, comprising:

a memory that stores computer-readable code; and

a processor operatively coupled to said memory, said processor configured to implement said computer-readable code, said computer-readable code configured to;

establish a rule defining said fraudulent event, said rule including at least one condition;

process at least one image of said retail location to identify said condition; and

perform a defined action if said rule is satisfied.

14. The system of claim 13, wherein said fraudulent event is a person stealing an item.

15. The system of claim 13, wherein said fraudulent event is a person attempting to return an item without a receipt.

16. A system for detecting a fraudulent event in a retail location, comprising:

a memory that stores computer-readable code; and

a processor operatively coupled to said memory, said processor configured to implement said computer-readable code, said computer-readable code configured to;

obtain at least one image of said retail location;

analyze said image using video content analysis techniques to identify at least one predefined feature in said image associated with said fraudulent event; and

perform a defined action if said rule is satisfied.

17. The system of claim 16, wherein said fraudulent event is a person stealing an item.

18. The system of claim 16, wherein said fraudulent event is a person attempting to return an item without a receipt.

19. An article of manufacture for detecting a fraudulent event in a retail location, comprising:

a computer readable medium having computer readable code means embodied thereon, said computer readable program code means comprising;

a step to establish a rule defining said fraudulent event, said rule including at least one condition;

a step to process at least one image of said retail location to identify said condition; and

a step to perform a defined action if said rule is satisfied.

20. An article of manufacture for detecting a fraudulent event in a retail location, comprising:

a computer readable medium having computer readable code means embodied thereon, said computer readable program code means comprising;

a step to obtain at least one image of said retail location;

a step to analyze said image using video content analysis techniques to identify at least one predefined feature in said image associated with said fraudulent event; and

a step to perform a defined action if said rule is satisfied.