Illumination Detection Using Classifier Chains

• US 20120207358A1
• Filed: 01/16/2012
• Published: 08/16/2012
• Est. Priority Date: 03/05/2007
• Status: Abandoned Application

• Current Assignee: DigitalOptics Corporation Europe Limited (Adeia Inc.)
• Original Assignee: DigitalOptics Corporation Europe Limited (Adeia Inc.)
• Inventors: Gangea, Mihnea, Corcoran, Peter, Blonk, Leendert
• Application Number:
  US13/351,177
• Publication Number:
  US 20120207358A1
• Time in Patent Office: Days
• US Class Current: 382/118
• CPC Class Codes: G06F 18/214 Generating training patterns; Bootstrap methods, e.g. bagging or boosting
• CPC Class Codes: G06V 10/60 relating to illumination properties, e.g. using a reflectance or lighting model
• CPC Class Codes: G06V 10/774 Generating sets of training patterns; Bootstrap methods, e.g. bagging or boosting
• CPC Class Codes: G06V 40/167 using comparisons between temporally consecutive images

Abstract

A face illumination normalization method includes acquiring a digital image including a face that appears to be illuminated unevenly. One or more uneven illumination classifier programs are applied to the face data to determine the presence of the face within the digital image and/or the uneven illumination condition of the face. The uneven illumination condition may be corrected to thereby generate a corrected face image appearing to have more uniform illumination, for example, to enhance face recognition.

Claims

1. A face detection method, comprising:

(a) acquiring a digital image

(b) extracting a sub-window from said image

(c) applying two or more shortened face detection classifier cascades, trained to be selectively sensitive to a characteristic of a face region,

(d) based on the applying, determining a probability that a face with a certain form of the characteristic is present within the sub-window;

(e) based on the determining, applying an extended face detection classifier cascade trained for sensitivity to said form of said characteristic;

(f) providing a final determination that a face exists within the image sub-window; and

(g) repeating steps (b)-(e) one or more times for one or more further sub-windows from the image or one or more further characteristics, or both.

2. The method of claim 1, wherein the characteristic or characteristics comprise a directional illumination of the face region, an in-plane rotation of the face region, a 3D pose variation of the face region. a degree of smile, a degree of eye-blinking, a degree of eye-winking, a degree of mouth opening, facial blurring, eye-defect, facial shadowing, facial occlusion, facial color, or facial shape, or combinations thereof.

3. The method of claim 1, wherein the characteristic comprises a directional illumination, and the method further comprises determining an uneven illumination condition by applying one or more uneven illumination classifier cascades.

4. The method of claim 3, further comprising applying a front illumination classifier cascade.

5. The method of claim 4, further comprising determining an illumination condition of a face within a sub-window based on acceptance by one of the classifier cascades.

6. The method of claim 5, wherein the digital image is one of multiple images in a series that include the face, and the method further comprises correcting an uneven illumination condition of the face within a different image in the series than said digital image within which the illuminating condition is determined.

7. The method of claim 3, wherein said uneven illumination classifier cascades comprise a top illumination classifier, a bottom illumination classifier, and one or both of right and left illumination classifiers.

8. An improved face detection method, comprising:

(a) acquiring a digital image

(b) extracting a sub-window from said image

(c) applying two or more shortened face detection classifier cascades, trained to be selectively sensitive to directional facial illumination;

(d) based on the applying, determining a probability that a face having a certain form of directional facial illumination is present within the sub-window;

(e) based on the determining, applying an extended face detection classifier cascade trained for sensitivity to said form of directional face illumination;

(f) providing a final determination that a face exists within the image sub-window

(g) repeating steps (b)-(e) one or more times for one or more further sub-windows from the image or one or more further directional facial illuminations, or both

9. The method of claim 8, wherein the digital image is one of multiple images in a series that include the face, and the method further comprises correcting an uneven illumination condition of the face within a different image in the series than said digital image within which the illuminating condition is determined.

10. The method of claim 8, wherein said uneven illumination classifier cascades comprise a top illumination classifier, a bottom illumination classifier, and one or both of right and left illumination classifiers.

11. The method of claim 10, further comprising applying a front illumination classifier cascade.

12. The method of claim 11, further comprising determining an illumination condition of a face within a sub-window based on acceptance by one of the classifier cascades.

13. A digital image acquisition device including an optoelectronic system for acquiring a digital image, and a digital memory having stored therein processor-readable code for programming the processor to perform a face illumination normalization method, wherein the method comprises:

(a) acquiring a digital image

(b) extracting a sub-window from said image

(c) applying two or more shortened face detection classifier cascades, trained to be selectively sensitive to a characteristic of a face region,

(d) based on the applying, determining a probability that a face with a certain form of the characteristic is present within the sub-window;

(e) based on the determining, applying an extended face detection classifier cascade trained for sensitivity to said form of said characteristic;

(f) providing a final determination that a face exists within the image sub-window; and

(g) repeating steps (b)-(e) one or more times for one or more further sub-windows from the image or one or more further characteristics, or both.

14. The device of claim 13, wherein the characteristic or characteristics comprise a directional illumination of the face region, an in-plane rotation of the face region, a 3D pose variation of the face region. a degree of smile, a degree of eye-blinking, a degree of eye-winking, a degree of mouth opening, facial blurring, eye-defect, facial shadowing, facial occlusion, facial color, or facial shape, or combinations thereof.

15. The device of claim 13, wherein the characteristic comprises a directional illumination, and the method further comprises determining an uneven illumination condition by applying one or more uneven illumination classifier cascades.

16. The device of claim 15, wherein the method further comprises applying a front illumination classifier cascade.

17. The device of claim 16, wherein the method further comprises determining an illumination condition of a face within a sub-window based on acceptance by one of the classifier cascades.

18. The device of claim 17, wherein the digital image is one of multiple images in a series that include the face, and the method further comprises correcting an uneven illumination condition of the face within a different image in the series than said digital image within which the illuminating condition is determined.

19. The device of claim 13, wherein said uneven illumination classifier cascades comprise a top illumination classifier, a bottom illumination classifier, and one or both of right and left illumination classifiers.

20. A digital image acquisition device including an optoelectronic system for acquiring a digital image, and a digital memory having stored therein processor-readable code for programming the processor to perform a face illumination normalization method, wherein the method comprises:

(a) acquiring a digital image

(b) extracting a sub-window from said image

(c) applying two or more shortened face detection classifier cascades, trained to be selectively sensitive to directional facial illumination;

(d) based on the applying, determining a probability that a face having a certain form of directional facial illumination is present within the sub-window;

(e) based on the determining, applying an extended face detection classifier cascade trained for sensitivity to said form of directional face illumination;

(f) providing a final determination that a face exists within the image sub-window

(g) repeating steps (b)-(e) one or more times for one or more further sub-windows from the image or one or more further directional facial illuminations, or both

21. The device of claim 20, wherein the digital image is one of multiple images in a series that include the face, and the method further comprises correcting an uneven illumination condition of the face within a different image in the series than said digital image within which the illuminating condition is determined.

22. The device of claim 20, wherein said uneven illumination classifier cascades comprise a top illumination classifier, a bottom illumination classifier, and one or both of right and left illumination classifiers.

23. The device of claim 22, wherein the method further comprises applying a front illumination classifier cascade.

24. The device of claim 23, wherein the method further comprises determining an illumination condition of a face within a sub-window based on acceptance by one of the classifier cascades.

25. A digital memory having stored therein processor-readable code for programming the processor to perform a face illumination normalization method, wherein the method comprises:

(a) acquiring a digital image

(b) extracting a sub-window from said image

(c) applying two or more shortened face detection classifier cascades, trained to be selectively sensitive to a characteristic of a face region,

(d) based on the applying, determining a probability that a face with a certain form of the characteristic is present within the sub-window;

(e) based on the determining, applying an extended face detection classifier cascade trained for sensitivity to said form of said characteristic;

(f) providing a final determination that a face exists within the image sub-window; and

(g) repeating steps (b)-(e) one or more times for one or more further sub-windows from the image or one or more further characteristics, or both.

26. The digital memory of claim 25, wherein the characteristic or characteristics comprise a directional illumination of the face region, an in-plane rotation of the face region, a 3D pose variation of the face region. a degree of smile, a degree of eye-blinking, a degree of eye-winking, a degree of mouth opening, facial blurring, eye-defect, facial shadowing, facial occlusion, facial color, or facial shape, or combinations thereof.

27. The digital memory of claim 25, wherein the characteristic comprises a directional illumination, and the method further comprises determining an uneven illumination condition by applying one or more uneven illumination classifier cascades.

28. The digital memory of claim 27, wherein the method further comprises applying a front illumination classifier cascade.

29. The digital memory of claim 28, wherein the method further comprises determining an illumination condition of a face within a sub-window based on acceptance by one of the classifier cascades.

30. The digital memory of claim 29, wherein the digital image is one of multiple images in a series that include the face, and the method further comprises correcting an uneven illumination condition of the face within a different image in the series than said digital image within which the illuminating condition is determined.

31. The digital memory of claim 25, wherein said uneven illumination classifier cascades comprise a top illumination classifier, a bottom illumination classifier, and one or both of right and left illumination classifiers.

32. A digital memory having stored therein processor-readable code for programming the processor to perform a face illumination normalization method, wherein the method comprises:

(a) acquiring a digital image

(b) extracting a sub-window from said image

(c) applying two or more shortened face detection classifier cascades, trained to be selectively sensitive to directional facial illumination;

(d) based on the applying, determining a probability that a face having a certain form of directional facial illumination is present within the sub-window;

(e) based on the determining, applying an extended face detection classifier cascade trained for sensitivity to said form of directional face illumination;

(f) providing a final determination that a face exists within the image sub-window

(g) repeating steps (b)-(e) one or more times for one or more further sub-windows from the image or one or more further directional facial illuminations, or both

33. The digital memory of claim 32, wherein the digital image is one of multiple images in a series that include the face, and the method further comprises correcting an uneven illumination condition of the face within a different image in the series than said digital image within which the illuminating condition is determined.

34. The digital memory of claim 32, wherein said uneven illumination classifier cascades comprise a top illumination classifier, a bottom illumination classifier, and one or both of right and left illumination classifiers.

35. The digital memory of claim 34, wherein the method further comprises applying a front illumination classifier cascade.

36. The digital memory of claim 35, wherein the method further comprises determining an illumination condition of a face within a sub-window based on acceptance by one of the classifier cascades.