HORIZONTAL GAZE ESTIMATION FOR VIDEO CONFERENCING

• US 20100208078A1
• Filed: 02/17/2009
• Published: 08/19/2010
• Est. Priority Date: 02/17/2009
• Status: Abandoned Application

• Current Assignee: Cisco Technology, Inc. (Cisco Systems, Inc.)
• Original Assignee: Cisco Technology, Inc. (Cisco Systems, Inc.)
• Inventors: Friel, Joseph T., Tian, Dihong, Mauchly, J. William
• Application Number:
  US12/372,221
• Publication Number:
  US 20100208078A1
• Time in Patent Office: Days
• US Class Current: 348/169
• CPC Class Codes: G06T 2207/10016 Video; Image sequence
• CPC Class Codes: G06T 2207/30201 Face
• CPC Class Codes: G06T 7/277 involving stochastic approaches, e.g. using Kalman filters
• CPC Class Codes: G06T 7/73 using feature-based methods
• CPC Class Codes: G06T 7/77 using statistical methods
• CPC Class Codes: G06V 40/19 Sensors therefor

Abstract

Techniques are provided to determine the horizontal gaze of a person from a video signal generated from viewing the person with at least one video camera. From the video signal, a head region of the person is detected and tracked. The dimensions and location of a sub-region within the head region is also detected and tracked from the video signal. An estimate of the horizontal gaze of the person is computed from a relative position of the sub-region within the head region.

Claims

1. A method comprising:

viewing at least a first person with at least a first video camera and producing a video signal therefrom;

detecting and tracking a head region of the first person in the video signal;

detecting and tracking dimensions and location of a sub-region within the head region in the video signal; and

computing an estimate of a horizontal gaze of the first person from a relative position of the sub-region within the head region.

2. The method of claim 1, wherein viewing comprises viewing the first person with the first video camera that is positioned with respect to a plurality of video display sections arranged to face the first person, and further comprising displaying video images of each of a plurality of persons on corresponding ones of the plurality of video display sections;

and determining towards which of the plurality of persons the first person is looking from the estimate of the horizontal gaze of the first person.

3. The method of claim 1, wherein viewing further comprises viewing a plurality of persons with the first video camera or another video camera, and further comprising determining towards which of the plurality of other persons the first person is looking from the estimate of the horizontal gaze of the first person.

4. The method of claim 1, wherein detecting and tracking the head region comprises generating data for a first rectangle that represents the head region of the first person, and wherein detecting and tracking the sub-region comprises generating data for dimensions and location of a second rectangle within the first rectangle, wherein the second rectangle comprises ears, nose and mouth of the first person.

5. The method of claim 4, wherein computing the estimate of the horizontal gaze comprising computing a distance d between horizontal centers of the first rectangle and the second rectangles, respectively, and a radius r of the first rectangle, and computing a horizontal gaze angle as arcsin(d/r).

6. The method of claim 1, wherein viewing comprises viewing at a first location a first group of persons that includes the first person with the first video camera and viewing at a second location a second group of persons with at least a second video camera, and further comprising displaying at the first location video images on respective video display sections of individual persons in the second group of persons based on a video signal output by the second video camera, and displaying at the second location video images on respective video display sections of individuals persons in the first group of persons based on the video signal output by the first video camera.

7. The method of claim 6, wherein computing comprises computing the estimate of the horizontal gaze of the first person with respect to another person in the first group of persons.

8. The method of claim 6, wherein computing comprises computing the estimate of the horizontal gaze of the first person with respect to a video display section showing a video image of a person in the second group of persons.

9. The method of claim 1, wherein computing comprises, at each time step:

computing a random sample particle distribution that represents the dimensions and location of the sub-region within the head region;

computing at least one image analysis feature of the sub-region;

computing importance weights for a proposed particle distribution based on the at least one image analysis feature;

computing a new sample particle distribution by emphasizing components of the sample particle distribution with high importance weights and de-emphasizing components of the sample particle distribution with low importance weights.

10. The method of claim 9, and further comprising computing an updated estimate of the dimensions and location of the sub-region within the head region as a weighted average of the new sample particle distribution.

11. The method of claim 9, and further comprising computing an updated estimate of the dimensions and locations of the sub-region within the head region based on a weighted average of components of the new sample particle distribution that have highest importance weights.

12. The method of claim 1, wherein detecting the head region, detecting the sub-region and computing are performed with respect to each of a plurality of persons so as to compute a common view from the horizontal gaze of each of the plurality of persons, and further comprising selecting a video signal containing an image of a particular person towards whom the common view is determined.

13. The method of claim 1, wherein detecting the head region, detecting the sub-region and computing are performed with respect to each of a plurality of persons so as to compute a common view from the horizontal gaze of each of the plurality of persons, and further comprising displaying a speaking person'"'"'s image on one section of a display and displaying in another section of the display an image of a person towards whom the common view is determined.

14. The method of claim 1, and further comprising processing a video image of the first person to artificially adjust eyeball direction of the first person.

15. The method of claim 1, and further comprising selecting for output to a display a signal from one of a plurality of video cameras based on the horizontal gaze of the first person.

16. Logic encoded in one or more tangible media for execution and when executed operable to:

detect and track a head region of a person from a video signal produced by a video camera that is configured to view a person;

detect and track dimensions and location of a sub-region within the head region in the video signal; and

compute an estimate of a horizontal gaze of the person from a relative position of the sub-region within the head region.

17. The logic of claim 16, wherein the logic that detects and tracks the head region comprises logic that is configured to generate data for a first rectangle that represents the head region of the person, and the logic that detects and tracks the sub-region comprises logic that is configured to generate data for dimensions and location of a second rectangle within the first rectangle, wherein the second rectangle comprises ears, nose and mouth of the person.

18. The logic of claim 17, wherein the logic that computes the estimate of the horizontal gaze comprises logic that is configured to compute a distance d between horizontal centers of the first rectangle and the second rectangles, respectively, and a radius r of the first rectangle, and to compute a horizontal gaze angle as arcsin(d/r).

19. The logic of claim 16, wherein the logic that computes the estimate of the horizontal gaze comprises logic that is configured to, at each time step:

compute a random sample particle distribution that represents the dimensions and location of the sub-region within the head region;

computes at least one image analysis feature of the sub-region;

computes importance weights for a proposed particle distribution based on the at least one image analysis feature;

computes a new sample particle distribution by emphasizing components of the sample particle distribution with high importance weights and de-emphasizing components of the sample particle distribution with low importance weights.

20. An apparatus comprising:

at least one video camera that is configured to view a person and to produce a video signal;

a processor that is configured to;

detect and track a head region of the person in the video signal;

detect and track dimensions and location of a sub-region within the head region in the video signal; and

compute an estimate of a horizontal gaze of the person from a relative position of the sub-region within the head region.

21. The apparatus of claim 20, wherein the processor is configured to detect and track the head region by generating data for a first rectangle that represents the head region of the person, and the processor is configured to detect and track the sub-region by generating data for dimensions and location of a second rectangle within the first rectangle, wherein the second rectangle comprises ears, nose and mouth of the person.

22. The apparatus of claim 21, wherein the processor is configured to compute the estimate of the horizontal gaze by computing a distance d between horizontal centers of the first rectangle and second rectangles, respectively, and a radius r of the first rectangle, and computing a horizontal gaze angle as arcsin(d/r).