Real-time face tracking in a digital image acquisition device

• US 8,744,145 B2
• Filed: 03/12/2013
• Issued: 06/03/2014
• Est. Priority Date: 08/11/2006
• Status: Active Grant

• Current Assignee: FotoNation Limited (Adeia Inc.)
• Original Assignee: DigitalOptics Corporation Europe Limited (Adeia Inc.)
• Inventors: Petrescu, Stefan, Corcoran, Peter, Steinberg, Eran, Bigioi, Petronel, Drimbarean, Alexandru
• Primary Examiner(s): Werner, Brian P
• Application Number:
  US13/797,989
• Publication Number:
  US 20130195319A1
• Time in Patent Office: 448 Days
• Field of Search: None
• US Class Current: 382/118
• CPC Class Codes: G06F 18/2148 characterised by the process organisation or structure, e.g. boosting cascade
• CPC Class Codes: G06V 30/19147 Obtaining sets of training patterns; Bootstrap methods, e.g. bagging or boosting
• CPC Class Codes: G06V 30/2504 Coarse or fine approaches, e.g. resolution of ambiguities or multiscale approaches
• CPC Class Codes: G06V 40/162 using pixel segmentation or colour matching
• CPC Class Codes: G06V 40/165 using facial parts and geometric relationships
• CPC Class Codes: G06V 40/167 using comparisons between temporally consecutive images
• CPC Class Codes: G06V 40/171 Local features and components; Facial parts eye characteristics G06V40/18; Occluding parts, e.g. glasses; Geometrical relationships
• CPC Class Codes: H04N 1/2112 using still video cameras
• CPC Class Codes: H04N 1/32112 in a separate computer file, document page or paper sheet, e.g. a fax cover sheet H04N1/32122 takes precedence
• CPC Class Codes: H04N 1/32128 attached to the image data, e.g. file header, transmitted message header, information on the same page or in the same computer file as the image for information embedded in the image H04N1/32144
• CPC Class Codes: H04N 2101/00 Still video cameras
• CPC Class Codes: H04N 2201/0084 Digital still camera
• CPC Class Codes: H04N 2201/3205 of identification information, e.g. name or ID code H04N2201/3209 takes precedence
• CPC Class Codes: H04N 23/61 based on recognised objects
• CPC Class Codes: H04N 23/611 where the recognised objects include parts of the human body
• CPC Class Codes: H04N 23/635 Region indicators; Field of view indicators
• CPC Class Codes: H04N 23/695 Control of camera direction for changing a field of view, e.g. pan, tilt or based on tracking of objects

Abstract

An image processing apparatus for tracking faces in an image stream iteratively receives an acquired image from the image stream including one or more face regions. The acquired image is sub-sampled at a specified resolution to provide a sub-sampled image. An integral image is then calculated for a least a portion of the sub-sampled image. Fixed size face detection is applied to at least a portion of the integral image to provide a set of candidate face regions. Responsive to the set of candidate face regions produced and any previously detected candidate face regions, the resolution is adjusted for sub-sampling a subsequent acquired image.

Claims

1. A method of detecting faces in an image stream, comprising:

receiving an acquired image from said image stream including one or more face regions;

sub-sampling said acquired image at a specified resolution to provide a sub-sampled image;

identifying one or more regions of said acquired image predominantly including skin tones by applying one of a number of filters to define said one or more regions of said acquired image predominantly including skin tones, at least one of said filters including a restrictive skin filter and at least one of said filters including a relaxed skin filter;

calculating a corresponding integral image for at least one of said one or more regions of said sub-sampled image;

applying face detection to at least a portion of said integral image to provide a set of one or more candidate face regions each having a given size and a respective location;

providing a quality measure for one of a candidate region of an image or said acquired image; and

responsive to said quality measure, applying said relaxed skin filter to a subsequently acquired image.

2. A method as claimed in claim 1, wherein responsive to failing to detect at least one face region for said image, the method further comprises enhancing the contrast of the luminance characteristics for at least a region corresponding to one of said skin tone regions in a subsequently acquired image.

3. A method as claimed in claim 1, wherein the applying face detection comprises acquiring each of multiple new acquired images with progressively increased exposure parameters until at least one candidate face region is detected.

4. An iterative method of detecting faces in an image stream, the method comprising:

receiving an acquired image from said image stream including one or more face regions;

sub-sampling said acquired image at a specified resolution to provide a sub-sampled image;

identifying one or more regions of said acquired image predominantly including skin tones by applying one of a number of filters to define said one or more regions of said acquired image predominantly including skin tones, at least one of said filters including a restrictive skin filter and at least one of said filters including a relaxed Skin filter;

calculating a corresponding integral image for at least one of said one or more regions of said sub-sampled image;

applying face detection to at least a portion of said integral image to provide a set of one or more candidate face regions each having a given size and a respective location,

wherein applying the face detection comprises applying relaxed face detection parameters;

providing a quality measure for one of a candidate region of an image or said acquired image; and

responsive to said quality measure, applying said relaxed skin filter to a subsequently acquired image.

5. An iterative method as claimed in claim 4, wherein responsive to failing to detect at least one face region for said image, the method further comprises enhancing the contrast of the luminance characteristics for at least a region corresponding to one of said skin tone regions in a subsequently acquired image.

6. An iterative method as claimed in claim 4, wherein the applying face detection comprises acquiring each of multiple new acquired images with progressively increased exposure parameters until at least one candidate face region is detected.

7. An image processing apparatus including one or more processors and one or more digital storage media having digitally-encoded instructions embedded therein for programming the one or more processors to perform an iterative method of detecting faces in an image stream, the method comprising:

receiving an acquired image from said image stream including one or more face regions;

sub-sampling said acquired image at a specified resolution to provide a sub-sampled identifying one or more regions of said acquired image predominantly including skin tones by applying one of a number of filters to define said one or more regions of said acquired image predominantly including skin tones, at least one of said filters including a restrictive skin filter and at least one of said filters including a relaxed skin filter;

calculating a corresponding integral image for at least one of said one or more regions of said sub-sampled image;

applying face detection to at least a portion of said integral image to provide a set of one or more candidate face regions each having a given size and a respective location;

providing a quality measure for one of a candidate region of an image or said acquired image; and

responsive to said quality measure, applying said relaxed skin filter to a subsequently acquired image.

8. An apparatus as claimed in claim 7, wherein responsive to failing to detect at least one face region for said image, the method further comprises enhancing the contrast of the luminance characteristics for at least a region corresponding to one of said skin tone regions in a subsequently acquired image.

9. An apparatus as claimed in claim 7, wherein the applying face detection comprises acquiring each of multiple new acquired images with progressively increased exposure parameters until at least one candidate face region is detected.

10. An image processing apparatus including one or more processors and one or more digital storage media having digitally-encoded instructions embedded therein for programming the one or more processors to perform an iterative method of detecting faces in an image stream, the method comprising:

receiving an acquired image from said image stream including one or more face regions;

sub-sampling said acquired image at a specified resolution to provide a sub-sampled identifying one or more regions of said acquired image predominantly including skin tones by applying one of a number of filters to define said one or more regions of said acquired image predominantly including skin tones, at least one of said filters including a restrictive skin filter and at least one of said filters including a relaxed skin filter;

calculating a corresponding integral image for at least one of said one or more regions of said sub-sampled image;

applying face detection to at least a portion of said integral image to provide a set of one or more candidate face regions each having a given size and a respective location,

wherein applying the face detection comprises applying relaxed face detection parameters;

providing a quality measure for one of a candidate region of an image or said acquired image; and

responsive to said quality measure, applying said relaxed skin filter to a subsequently acquired image.

11. An apparatus as claimed in claim 10, wherein responsive to failing to detect at least one face region for said image, the iterative method further comprises enhancing the contrast of the luminance characteristics for at least a region corresponding to one of said skin tone regions in a subsequently acquired image.

12. An apparatus as claimed in claim 10, wherein the applying face detection comprises acquiring each of multiple new acquired images with progressively increased exposure parameters until at least one candidate face region is detected.

13. One or more non-transitory processor-readable digital storage media having digitally-encoded instructions embedded therein for programming one or more processors to perform a method of detecting faces in an image stream, the method comprising:

receiving an acquired image from said image stream including one or more face regions;

sub-sampling said acquired image at a specified resolution to provide a sub-sampled image;

identifying one or more regions of said acquired image predominantly including skin tones by applying one of a number of filters to define said one or more regions of said acquired image predominantly including skin tones, at least one of said filters including a restrictive skin filter and at least one of said filters including a relaxed skin filter;

calculating a corresponding integral image for at least one of said one or more regions of said sub-sampled image;

applying face detection to at least a portion of said integral image to provide a set of one or more candidate face regions each having a given size and a respective location;

providing a quality measure for one of a candidate region of an image or said acquired image; and

responsive to said quality measure, applying said relaxed skin filter to a subsequently acquired image.

14. One or more non-transitory processor-readable digital storage media as claimed in claim 13, wherein responsive to failing to detect at least one face region for said image, the method further comprises enhancing the contrast of the luminance characteristics for at least a region corresponding to one of said skin tone regions in a subsequently acquired image.

15. One or more non-transitory processor-readable digital storage media as claimed in claim 13, wherein the applying face detection comprises acquiring each of multiple new acquired images with progressively increased exposure parameters until at least one candidate face region is detected.

16. One or more non-transitory processor-readable digital storage media having digitally-encoded instructions embedded therein for programming one or more processors to perform a method of detecting faces in an image stream, the method comprising:

receiving an acquired image from said image stream including one or more face regions;

sub-sampling said acquired image at a specified resolution to provide a sub-sampled image;

identifying one or more regions of said acquired image predominantly including skin tones by applying one of a number of filters to define said one or more regions of said acquired image predominantly including skin tones, at least one of said filters including a restrictive skin filter and at least one of said filters including a relaxed skin filter;

calculating a corresponding integral image for at least one of said one or more regions of said sub-sampled image;

applying face detection to at least a portion of said integral image to provide a set of one or more candidate face regions each having a given size and a respective location,

wherein applying the face detection comprises applying relaxed face detection parameters;

providing a quality measure for one of a candidate region of an image or said acquired image; and

responsive to said quality measure, applying said relaxed skin filter to a subsequently acquired image.

17. One or more non-transitory processor-readable digital storage media as claimed in claim 16, wherein responsive to failing to detect at least one face region for said image, the method further comprises enhancing the contrast of the luminance characteristics for at least a region corresponding to one of said skin tone regions in a subsequently acquired image.

18. One or more non-transitory processor-readable digital storage media as claimed in claim 16, wherein the applying face detection comprises acquiring each of multiple new acquired images with progressively increased exposure parameters until at least one candidate face region is detected.