System for detecting skin-tone regions within an image

• US 6,332,033 B1
• Filed: 08/14/2000
• Issued: 12/18/2001
• Est. Priority Date: 01/08/1998
• Status: Expired due to Fees

• Current Assignee: Sharp Kabushiki Kaisha (Hon Hai Precision Industry Co., Ltd.)
• Original Assignee: Sharp Laboratories of America Incorporated (Hon Hai Precision Industry Co., Ltd.)
• Inventors: Qian, Richard
• Primary Examiner(s): Bella, Matthew C.
• Assistant Examiner(s): CHAWAN, SHEELA C
• Application Number:
  US09/638,732
• Time in Patent Office: 491 Days
• Field of Search: 382/103, 382/118, 382/156, 382/164, 382/190, 382/193, 382/209, 382/274, 382/276, 382/282, 382/283
• US Class Current: 382/124
• CPC Class Codes: G06T 2207/10016 Video; Image sequence
• CPC Class Codes: G06T 2207/10024 Color image
• CPC Class Codes: G06T 2207/30201 Face
• CPC Class Codes: G06T 7/90 Determination of colour characteristics
• CPC Class Codes: G06V 40/162 using pixel segmentation or colour matching

Abstract

A system detects a face within an image by receiving the image which includes a plurality of pixels, where a plurality of the pixels of the image is represented by respective groups of at least three values. The image is filtered by transforming a plurality of the respective groups of the at least three values to respective groups of less than three values, where the respective groups of the less than three values has less dependency on brightness than the respective groups of the at least three values. Regions of the image representative of skin-tones are determined based on the filtering. A first distribution of the regions of the image representative of the skin-tones in a first direction is calculated. A second distribution of the regions of the image representative of the skin-tones in a second direction is calculated, where the first direction and the second direction are different. The face within the image is located based on the first distribution and the second distribution. The estimated face location may also be used for tracking the face between frames of a video.

Claims

1. A method of detecting a skin-tone image comprising the steps of:

(a) receiving said image including a plurality of pixels, where a plurality of said pixels of said image is represented by respective groups of at least three values;

(b) filtering said image by transforming a plurality of said respective groups of said at least three values, where said respective groups of said less than three values has less dependency on brightness than said respective groups of said at least three values;

(c) determining regions of aid image representative of skin-tones based on said filtering of step (b);

(d) calculating a first distribution of said regions of said image representative of said skin-tones in a first direction;

(e) calculating a second distribution of said regions of said image representative of said skin-tones in a second direction, where said first direction and said second direction are different, the alignment of said first direction does not change based on the color distribution of said image, and the alignment of said second direction does not change based on the color distribution of said image; and

(f) locating said skin-tone region within said image based on said first distribution and said second distribution.

2. The method of claim 1 where said image includes from a video containing multiple images.

3. The method of claim 1 where said image includes a human face.

4. The method of claim 1 where said at least three values includes a red value, a green value, and a blue value.

5. The method of claim 4 where said respective groups of less than three values includes, a r value defined by said red value divided by the summation of said red value, said green value, and said blue value, and a g value defined by said green value divided by the summation of said red value, said green value, and said blue value.

6. The method of claim 1 wherein at least one of said regions is an individual pixel of said image.

7. The method of claim 1 wherein said determining of step (c) is based on a polygonal shape.

8. The method of claim 1 wherein said determining of step (c) is based on a circle.

9. The method of claim 1 wherein at least one of said first distribution and said second distribution is a histogram.

10. The method of claim 1 wherein said first distribution is in a x-direction.

11. The method of claim 10 wherein said second distribution is in a y-direction.

12. The method of claim 11 wherein said first distribution and said second distribution are in orthogonal directions.

13. The method of claim 1 wherein said first distribution and said second distribution are independent of each other.

14. The method of claim 1 further comprising the steps of:

(a) calculating a first generally central location of said first distribution;

(b) calculating a first generally central location of said second distribution; and

(c) locating said skin-tone region based on said first generally central location of said first distribution and said first generally central location of said second distribution.

15. The method of claim 14 wherein at least one of said first generally central location of said first distribution and said first generally central location of said second distribution is a mean.

16. The method of claim 14 wherein the size of said skin-tone region is based on the variance of said first distribution and the variance of said second distribution.

17. The method of claim 1 wherein said skin-tone region is tracked between subsequent frames.

18. The method of claim 17 wherein jitter movement of said skin-tone region is reduced between said subsequent frames.

19. A method of detecting a skin-tone region within an image comprising the steps of:

(a) receiving said image including a plurality of pixels, where a plurality of said pixels of said image is represented by respective groups of at least three values;

(b) filtering said image by transforming a plurality of said respective groups of said at least three values in said first color space to respective groups of less than three values in a second color space where said respective groups of said less than three values has less dependency on brightness than said respective groups of said at least three values;

(c) determining regions of said image representative of skin-tones based on said filtering of step (b);

(d) calculating a first distribution of said regions of said image representative of said skin-tones in a first direction in said first color space;

(e) calculating a second distribution of said regions of said image representative of said skin-tones in a second direction in said first color space, where said first direction and second direction are different; and

(f) locating said skin-tones region within said image based on said first distribution and said second distribution.

20. The method of claim 19 where said image includes from a video containing multiple images.

21. The method of claim 19 where said image includes a human face.

22. The method of claim 19 where said first and second direction are independent of the color distribution of said image.

23. The method of claim 19 where said first and second directions are temporarily the same.

24. The method of claim 19 wherein at least one of said regions is an individual pixel of said image.

25. The method of claim 19 wherein said determining of step (c) is based on a polygonal shape.

26. The method of claim 19 wherein said determining of step (c) is based on a circle.

27. The method of claim 19 wherein at least one of said first distribution and said second distribution is a histogram.

28. The method of claim 19 wherein said first distribution is in a x-direction.

29. The method of claim 28 wherein said second distribution is in a y-direction.

30. The method of claim 29 wherein said first distribution and said second distribution are in orthogonal directions.

31. The method of claim 19 wherein said first distribution and said second distribution are independent of each other.

32. The method of claim 19 further comprising the steps of:

(a) calculating a first generally central location of said first distribution;

(b) calculating a first generally central location of said second distribution; and

(c) locating said skin-tone region based on said first generally central location of said first distribution and said first generally central location of said second distribution.

33. The method of claim 32 wherein at least one of said first generally central location of said first distribution and said first generally central location of said second distribution is a mean.

34. The method of claim 32 wherein the size of said skin-tone region is based on the variance of said first distribution and the variance of said second distribution.

35. The method of claim 19 wherein said skin-tone region is tracked between subsequent frames.

36. The method of claim 35 wherein jitter movement of said skin-tone region is reduced between said subsequent frames.

37. A method of detecting a skin-tone region within an image comprising the steps of:

(a) receiving said image including a plurality of pixels of said image is represented by respective groups of at last three values;

(b) filtering said image by transforming a plurality of said respective groups of said at least three values to respective groups of less than three values, where said respective groups of said less than three values has less dependency on brightness than said respective groups of said at least three values;

(c) determining regions of said image representative of skin-tones based on said filtering of step (b) and based on at least one of a polygonal shape and a circle;

(d) calculating a first distribution of said regions of said image representative of said skin-tones in a first direction;

(e) calculating a second distribution of said regions of said image representative of said skin-tones in a second direction, where said first direction and said second direction are different; and

(f) locating said skin-tone region within said image based on said first distribution and said second distribution.

38. The method of claim 37 where said image includes from a video containing multiple images.

39. The method of claim 37 where said image includes a human face.

40. The method of claim 37 where said at least three values includes a red value, a green value, and a blue value.

41. The method of claim 40 where said respective groups of less than three values includes, a r value defined by said red value divided by the summation of said red value, said green value, and said blue value, and a g value defined by said green value divided by the summation of said red value, said green value, and said blue value.

42. The method of claim 37 wherein at least one of said regions is an individual pixel of said image.

43. The method of claim 37 wherein said determining of step (c) is based on a polygonal shape.

44. The method of claim 37 wherein said determining of step (c) is based on a circle.

45. The method of claim 37 wherein at least one of said first distribution and said second distribution is a histogram.

46. The method of claim 37 wherein said first distribution is in a x-direction.

47. The method of claim 46 wherein said second distribution is in a y-direction.

48. The method of claim 47 wherein said first distribution and said second distribution are in orthogonal directions.

49. The method of claim 37 wherein said first distribution and said second distribution are independent of each other.

50. The method of claim 37 further comprising the steps of:

(a) calculating a first generally central location of said first distribution;

(b) calculating a first generally central location of said second distribution; and

(c) locating said skin-tone region based on said first generally central location of said first distribution and said first generally central location of said second distribution.

51. The method of claim 50 wherein at least one of said first generally central location of said first distribution and said first generally central location of said second distribution is a mean.

52. The method of claim 50 wherein the size of said skin-tone region is based on the variance of said first distribution and the variance of said second distribution.

53. The method of claim 51 wherein said skin-tone region is tracked between subsequent frames.

54. The method of claim 53 wherein jitter movement of said skin-tone region is reduced between said subsequent frames.

57. The method of claim 54 where said image includes a human face.

55. A method of detecting a skin-tone region within an image comprising the steps of:

(a) receiving said image in an image color space including a plurality of pixels, where a plurality of said pixels of said image is represented by respective groups of at least three values;

(b) filtering said image by transforming a plurality of said respective groups of said at least three values to respective groups of less than three values in a transformed color space, where said respective groups of said less than three values has less dependency on brightness than said respective groups of said at least three values;

(c) determining pixels in said image color space representative of skin-tones based on said filtering of step (b);

(d) calculating a first distribution of said pixels of said image representative of said skin-tones in a first direction,

(e) calculating a second distribution of said pixels of said image representative of said skin-tones in a second direction, where said first direction and said second direction are different and said first direction and said second direction are the same; and

(f) locating said skin-tone region within said image color space based on said first distribution and said second distribution.

56. The method of claim 55 where said image includes from a video containing multiple images.

58. The method of claim 55 where said at least three values includes a red value, a green value, and a blue value.

59. The method of claim 58 where said respective groups of less than three values includes, a r value defined by said red value divided by the summation of said red value, said green value divided by the summation of said red value, said green value, and said blue value.

60. The method of claim 55 wherein at least one of said regions is an individual pixel of said image.

61. The method of claim 55 wherein said determining of step (c) is based on a polygonal shape.

62. The method of claim 55 wherein said determining of step (c) is based on a circle.

63. The method of claim 55 wherein at least one of said first distribution and said second distribution is a histogram.

64. The method of claim 55 wherein said first distribution is in a x-direction.

65. The method of claim 64 wherein said second distribution is in a y-direction.

66. The method of claim 65 wherein said first distribution and said second distribution are in orthogonal directions.

67. The method of claim 55 wherein said first distribution and said second distribution are independent of each other.

68. The method of claim 55 further comprising the steps of:

(a) calculating a first generally central location of said first distribution;

(b) calculating a first generally central location of said second distribution; and

(c) locating said skin-tone region based on said first generally central location of said first distribution and said first generally central location of said second distribution.

69. The method of claim 68 wherein at least one of said first generally central location of said first distribution and said first generally central location of said second distribution is a mean.

70. The method of claim 68 wherein the size of said skin-tone region is based on the variance of said first distribution and the variance of said second distribution.

71. The method of claim 55 wherein said skin-tone region is tracked between subsequent frames.

72. The method of claim 71 wherein jitter movement of said skin-tone region is reduced between said subsequent frames.