Visual tracking using depth data

• US 20050031166A1
• Filed: 05/28/2004
• Published: 02/10/2005
• Est. Priority Date: 05/29/2003
• Status: Active Grant

• Current Assignee: Honda Motor Co., Ltd. (Honda Motor Company)
• Original Assignee: Honda Motor Co., Ltd. (Honda Motor Company)
• Inventors: Fujimura, Kikuo, Nanda, Harsh
• Granted Patent: US 7,372,977 B2
• Time in Patent Office: Days
• US Class Current: 382/103
• CPC Class Codes: G06T 7/20 Analysis of motion motion estimation for coding, decoding, compressing or decompressing digital video signals H04N19/43, H04N19/51
• CPC Class Codes: G06V 10/24 Aligning, centring, orientation detection or correction of the image
• CPC Class Codes: G06V 40/103 Static body considered as a whole, e.g. static pedestrian or occupant recognition
• CPC Class Codes: G06V 40/107 Static hand or arm

Abstract

Real-time visual tracking using depth sensing camera technology, results in illumination-invariant tracking performance. Depth sensing (time-of-flight) cameras provide real-time depth and color images of the same scene. Depth windows regulate the tracked area by controlling shutter speed. A potential field is derived from the depth image data to provide edge information of the tracked target. A mathematically representable contour can model the tracked target. Based on the depth data, determining a best fit between the contour and the edge of the tracked target provides position information for tracking. Applications using depth sensor based visual tracking include head tracking, hand tracking, body-pose estimation, robotic command determination, and other human-computer interaction systems.

Claims

1. A computer based method for tracking a target using a depth sensing camera, the method comprising the steps of:

receiving a depth image of an area including the target to be tracked;

determining an edge of the target in the depth image; and

determining a best fit of a mathematically representable contour with respect to the determined edge corresponding to the target to be tracked.

2. The computer based method of claim 1, wherein determining the edge comprises comparing depth values of a plurality of depth image sections to find edge depth image sections having depth variations above a maximum threshold with respect to neighboring depth image sections.

3. The method of claim 2, wherein determining the edge further, comprises:

assigning a reference value to the edge depth image sections; and

assigning a value to neighboring depth image sections by applying a transform to calculate a metric from the closest edge depth image section.

4. The method of claim 3, wherein the depth image sections are depth image pixels.

5. The method of claim 1, wherein determining the edge comprises calculating a depth gradient vector.

6. The method of claim 1, wherein the mathematically representable contour is a graphically representable mathematical function.

7. The method of claim 6, wherein the mathematically representable contour is one of the group consisting of a parallelogram, an oval, an ellipse, a circle, and a curve.

8. The method of claim 1, wherein the target includes one or more body parts.

9. The method of claim 8, wherein the one or more body parts include a human head.

10. The method of claim 1, wherein the determining a best fit further comprises:

calculating a plurality of match values, one match value for each state of a set of possible states, the match values corresponding to an overall distance metric between the mathematically representable contour and the edge of the target in the depth image;

comparing the plurality of match values; and

selecting the state with the match value corresponding the distance metric signifying the smallest distance between the contour and the edge of the target.

11. The method of claim 1 further comprising:

determining a search area of the depth image in which to try different locations for the outline for determining the best fit.

12. The method of claim 11, wherein determining the search area comprises predicting a target position for a next image frame based on a constant velocity assumption for movement of the target.

13. A computer readable medium for tracking a target using a depth sensing camera comprising a computer program that when executed by a computer processor implements the steps of:

receiving a depth image of an area including the target to be tracked;

determining an edge of the target in the depth image; and

determining a best fit of a mathematically representable contour with respect to the determined edge corresponding to the target to be tracked.

14. A system for tracking a target using a depth sensing camera, the system comprising:

means for receiving a depth image of an area including the target to be tracked;

means for determining an edge of the target in the depth image; and

means for determining a best fit of a mathematically representable contour with respect to the determined edge corresponding to the target to be tracked.

15. A human-computer interaction system for visually tracking human movement comprising:

an active depth sensor for capturing depth images of human body parts;

a processing unit coupled to the active depth sensor for receiving the depth images, the processing unit comprising;

an edge detection module; and

a tracking module coupled to the edge detection module to determine a best fit of a mathematically representable contour with respect to one or more body parts to determine a position of the one or more body parts within the captured depth images.

16. The human-computer interaction system of claim 15, wherein the processing unit further comprises a body-lean determination module coupled to the tracking module to receive the determined position of the one or more body parts and configured to calculate a distance of each of the one or more body parts with respect to the active sensor and to relate the distance of each body part with respect to other body parts to determine lean data including the position of the body parts with respect to each other.

17. The human-computer interaction system of claim 15, wherein the lean data is sent to a control logic configured to determine whether to deploy an air-bag in a vehicle.

18. The human-computer interaction system of claim 15, wherein the position of the one or more body parts is used to provide user control input to a software application.

19. The human-computer interaction system of claim 18, wherein the software application is a computer game.

20. A motor vehicle configured to track occupant body-lean information, the motor vehicle comprising:

an active depth sensor for capturing depth images of human body parts;

a processing unit coupled to the active depth sensor for receiving the depth images, the processing unit comprising;

an edge detection module; and

a tracking module coupled to the edge detection module to determine a best fit of a mathematically representable contour with respect to one or more body parts to determine a position of the one or more body parts within the captured depth images.

21. The motor vehicle of claim 20, further comprising a body-lean determination module coupled to the tracking module to receive the determined position of the one or more body parts and configured to calculate a distance of each of the one or more body parts with respect to the active sensor and to relate the distance of each body part with respect to other body parts to determine lean data including the position of the body parts with respect to each other.

22. The motor vehicle of claim 21, wherein the lean data is sent to a control logic configured to determine whether to deploy an air-bag in the motor vehicle.