Facial surveillance system and method

• US 20040223629A1
• Filed: 05/06/2003
• Published: 11/11/2004
• Est. Priority Date: 05/06/2003
• Status: Abandoned Application

• Current Assignee: Viswis Incorporated
• Original Assignee: Viswis Incorporated
• Inventors: Chang, Jung-Chou
• Application Number:
  US10/429,720
• Publication Number:
  US 20040223629A1
• Time in Patent Office: Days
• US Class Current: 382/118
• CPC Class Codes: G06V 40/161 Detection; Localisation; Normalisation
• CPC Class Codes: G06V 40/40 Spoof detection, e.g. liveness detection
• CPC Class Codes: G07C 9/37 using biometric data, e.g. fingerprints, iris scans or voice recognition

Abstract

The present invention discloses a facial surveillance system and method. In this system and method, if a plurality of facial features can be found on a candidate facial area, further detection will be carried out to find any anomaly feature such as a mask, sun glasses or a helmet. Accordingly, potential criminal events may be effectively prevented.

Claims

1. A facial surveillance system, comprising:

an image processing means for finding a candidate facial area from an image;

a facial feature detection means for detecting if said candidate facial area contains a plurality of facial features;

an anomaly feature detection means for detecting if said candidate facial area contains at least one anomaly feature; and

a decision means for determining whether a valid or invalid face is detected based upon results of said facial feature detection means and/or said anomaly feature detection means.

2. The facial surveillance system of claim 1, wherein said image processing means finds said candidate facial area by neural network analysis.

3. The facial surveillance system of claim 1, wherein said image processing means finds said candidate facial area by principal component analysis (PCA) or eigentemplates.

4. The facial surveillance system of claim 1, wherein said anomaly feature detection means is to detect an object covering at least one of said facial features.

5. The facial surveillance system of claim 1, wherein said anomaly feature detection means is to detect at least one of dark sun glasses, a mask and a helmet on said candidate facial area.

6. The facial surveillance system of claim 1, which further comprises a signal receiving means for receiving a decision signal from said decision means.

7. The facial surveillance system of claim 6, wherein said signal receiving means is an access controller.

8. The facial surveillance system of claim 6, wherein said signal receiving means is a data storage means.

9. The facial surveillance system of claim 6, wherein said signal receiving means is a printing device.

10. A facial surveillance method, comprising steps of:

a) processing an image to find a candidate facial area;

b) determining if said candidate facial area contains a plurality of facial features, if yes, go to step c), and if not, skip to step d);

c) determining if said candidate facial area contains at least one anomaly feature or none; and

d) outputting a signal based upon said step b) and/or step c).

11. The facial surveillance method of claim 10, wherein said step a) is achieved by neural networks analysis.

12. The facial surveillance method of claim 10, wherein said step a) is achieved by principal component analysis (PCA) or eigentemplate analysis.

13. The facial surveillance method of claim 10, wherein said step b) is achieved by neural networks analysis.

14. The facial surveillance method of claim 10, wherein said step b) is achieved by principal component analysis (PCA) or eigentemplate analysis.

15. The facial surveillance method of claim 10, wherein said step c) is to detect an object covering at least one of said facial features.

16. The facial surveillance method of claim 10, wherein said step c) is to detect at least one of dark sun glasses, a mask, a helmet.

17. The facial surveillance method of claim 10, wherein said step c) is achieved by neural network analysis.

18. The facial surveillance method of claim 10, wherein said step c) is achieved by color analysis, texture analysis or shape analysis.

19. The facial surveillance method of claim 10, wherein said step d) is to output said signal to an access controller.

20. The facial surveillance method of claim 10, wherein said step d) is to output said signal to a storage means.

21. The facial surveillance method of claim 10, wherein said step d) is to output said signal to a printing device.