Statistical modeling and performance characterization of a real-time dual camera surveillance system

• US 20070019073A1
• Filed: 07/12/2006
• Published: 01/25/2007
• Est. Priority Date: 06/12/2000
• Status: Abandoned Application

• Current Assignee: Siemens Corporate Research Incorporated (Siemens AG)
• Original Assignee: Siemens Corporate Research Incorporated (Siemens AG)
• Inventors: Ramesh, Visvanathan, Comaniciu, Dorin, Greiffenhagen, Michael
• Application Number:
  US11/484,994
• Publication Number:
  US 20070019073A1
• Time in Patent Office: Days
• US Class Current: 348/148
• CPC Class Codes: G06T 2207/30196 Human being; Person
• CPC Class Codes: G06T 2207/30232 Surveillance
• CPC Class Codes: G06T 2207/30241 Trajectory
• CPC Class Codes: G06T 7/277 involving stochastic approaches, e.g. using Kalman filters
• CPC Class Codes: G06T 7/77 using statistical methods
• CPC Class Codes: G08B 13/19604 involving reference image or background adaptation with time to compensate for changing conditions, e.g. reference image update on detection of light level change
• CPC Class Codes: G08B 13/19608 Tracking movement of a target, e.g. by detecting an object predefined as a target, using target direction and or velocity to predict its new position
• CPC Class Codes: G08B 13/19628 of wide angled cameras and camera groups, e.g. omni-directional cameras, fish eye, single units having multiple cameras achieving a wide angle view
• CPC Class Codes: G08B 13/19641 Multiple cameras having overlapping views on a single scene
• CPC Class Codes: G08B 13/19643 wherein the cameras play different roles, e.g. different resolution, different camera type, master-slave camera
• CPC Class Codes: G08B 13/19647 Systems specially adapted for intrusion detection in or around a vehicle
• 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
• CPC Class Codes: H04N 7/181 for receiving images from a plurality of remote sources

Abstract

The present invention relates to a method for visually detecting and tracking an object through a space. The method chooses modules for a restricting a search function within the space to regions with a high probability of significant change, the search function operating on images supplied by a camera. The method also derives statistical models for errors, including quantifying an indexing step performed by an indexing module, and tuning system parameters. Further the method applies a likelihood model for candidate hypothesis evaluation and object parameters estimation for locating the object.

Claims

1. A surveillance method, comprising:

determining a location of an object with a first camera;

determining an uncertainty of the location of the object; and

controlling a characteristic of a second camera in accordance with the uncertainty.

2. The method of claim 1, wherein the first camera includes a camera and a parabolic mirror and the second camera is a pan-tilt camera.

3. The method of claim 1, wherein the characteristic of the second camera is zoom.

4. The method of claim 1, further comprising controlling one or more additional characteristics of the second camera in accordance with the uncertainty.

5. The method of claim 4, wherein the first characteristic is zoom and the one or more characteristics are pan and tilt.

6. The method of claim 1, wherein the characteristic of the second camera is also controlled in accordance with the location.

7. The method of claim 3, wherein the second camera zooms in as uncertainty decreases.

8. The method of claim 5, wherein the object is a person'"'"'s face and the controlling step is performed so that a probability that the person'"'"'s face is captured by the second camera is within a user specified probability.

9. A system for monitoring an object, comprising:

a first camera;

a second camera;

a processor that determines an uncertainty of a location of the object and controls a characteristic of the second camera in accordance with the uncertainty.

10. The system of claim 9, wherein the first camera includes a camera and a parabolic mirror and the second camera is a pan-tilt camera.

11. The system of claim 9, wherein the characteristic of the second camera is zoom.

12. The method of claim 9, further comprising controlling one or more additional characteristics of the second camera in accordance with the uncertainty.

13. The method of claim 12, wherein the first characteristic is zoom and the one or more characteristics are pan and tilt.

14. The system of claim 9, wherein the characteristic of the second camera is also controlled in accordance with the location.

15. The system of claim 11, wherein the second camera zooms in as uncertainty decreases.

16. The method of claim 9, wherein the object is a person'"'"'s face and the controlling step is performed so that a probability that the person'"'"'s face is captured by the second camera is within a user specified probability.

17. A system for tracking and detecting objects, comprising:

an automobile; and

an omnidirectional camera mounted in the automobile.

18. The system of claim 17, further comprising a parabolic mirror mounted in the automobile that interfaces with the omnidirectional camera to provide a panoramic view.

19. The system of claim 18, further comprising a pan-tilt camera mounted in the automobile.

20. The system of claim 19, wherein the pan-tilt camera is controlled in accordance with an output of the omnidirectional camera.

21. The system of claim 20, wherein a zoom characteristic of the pan-tilt camera is controlled.

22. A method for locating an object near an automobile, comprising:

creating a panoramic view with a parabolic mirror located in the automobile; and

capturing the panoramic view from the parabolic mirror with an omnidirectional camera located in the automobile.

23. The method of claim 22, further comprising processing the panoramic view to determine a location of the object.

24. The method of claim 23, further comprising controlling a pan-tilt camera based on the location of the object.

25. The method of claim 24, further comprising controlling a zoom characteristic of a pan-tilt camera based on the location of the object.

26. The method of claim 25, further comprising determining an uncertainty of the location and controlling a zoom characteristic of a pan-tilt camera based on the uncertainty.

27. A method of locating an object, comprising:

defining a plurality of statistical models of a scene;

defining one or more tasks to be performed;

translating the plurality of statistical models and the one or more tasks to specify one or more index functions that generate one or more hypotheses of object location candidates;

optimizing one or more parameters of each of the one or more index functions; and

creating an estimate that will follow use of the one or more index functions to verify the one or more hypotheses and to estimate object parameters.

28. The method of claim 27, wherein the estimate is used to generate uncertainty estimates.

29. The method of claim 28, comprising controlling a pan-tilt-zoom of a camera based on the uncertainty estimates.

30. The method of claim 29, comprising setting parameters of a sensor system based on the analysis of the behavior of the one or more index functions.

31. The method of claim 27, wherein the one or more tasks includes object detection, object localization and/or object tracking.

32. The method of claim 27, wherein the plurality of models are selected from the group consisting of:

a calibration model, an illumination invariant model, a background adaptation model, an object geometry model, a camera geometry model, an error model and an illumination model.