METHOD OF TRACKING AN OBJECT CAPTURED BY A CAMERA SYSTEM

• US 20120274777A1
• Filed: 07/06/2012
• Published: 11/01/2012
• Est. Priority Date: 03/03/2008
• Status: Active Grant

• Current Assignee: Motorola Solutions, Inc.
• Original Assignee: VideoIQ, Inc. (Motorola Solutions, Inc.)
• Inventors: Saptharishi, Mahesh, Lisin, Dimitri A.
• Granted Patent: US 8,655,020 B2
• Time in Patent Office: Days
• US Class Current: 348/159
• CPC Class Codes: G06F 18/22 Matching criteria, e.g. proximity measures
• CPC Class Codes: G06F 2218/12 Classification; Matching
• CPC Class Codes: G06T 2207/10016 Video; Image sequence
• CPC Class Codes: G06T 2207/30232 Surveillance
• CPC Class Codes: G06T 7/246 using feature-based methods, e.g. the tracking of corners or segments
• CPC Class Codes: G06T 7/73 using feature-based methods
• CPC Class Codes: G06V 20/41 Higher-level, semantic clustering, classification or understanding of video scenes, e.g. detection, labelling or Markovian modelling of sport events or news items segmenting video sequences G06V20/49
• CPC Class Codes: G06V 20/52 Surveillance or monitoring of activities, e.g. for recognising suspicious objects recognising microscopic objects G06V20/69
• CPC Class Codes: H04N 23/611 where the recognised objects include parts of the human body
• CPC Class Codes: H04N 23/63 by using electronic viewfinders
• CPC Class Codes: H04N 23/631 Graphical user interfaces [GUI] specially adapted for controlling image capture or setting capture parameters
• CPC Class Codes: H04N 23/66 Remote control of cameras or camera parts, e.g. by remote control devices
• CPC Class Codes: H04N 23/661 Transmitting camera control signals through networks, e.g. control via the Internet
• CPC Class Codes: H04N 7/18 Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
• CPC Class Codes: H04N 7/181 for receiving images from a plurality of remote sources

Abstract

A camera system comprises an image capturing device, object detection module, object tracking module, and match classifier. The object detection module receives image data and detects objects appearing in one or more of the images. The object tracking module temporally associates instances of a first object detected in a first group of the images. The first object has a first signature representing features of the first object. The match classifier matches object instances by analyzing data derived from the first signature of the first object and a second signature of a second object detected in a second image. The second signature represents features of the second object derived from the second image. The match classifier determine whether the second signature matches the first signature. A training process automatically configures the match classifier using a set of possible object features.

Claims

1. A method of tracking an object captured by a camera system, the method comprising:

receiving image data representing first and second images of a field of view of the camera system;

detecting a first object captured in the first image and a second object captured in the second image;

producing a first signature of the first object and a second signature of the second object, the first signature representing a first set of features of the first object and the second signature representing a second set of features of the second object;

producing data derived from the first and second signatures, the data corresponding to a first subset of features selected from the first set and a second subset of features selected from the second set; and

analyzing the data to determine whether the second object is an instance of the first object.

2. The method of claim 1, further comprising determining that the second object is an instance of the first object.

3. The method of claim 1, further comprising generating the second signature in real time.

4. The method of claim 1, further comprising combining portions of the first and second signatures to produce the data.

5. The method of claim 4, wherein the data are analyzed by a match classifier, and the match classifier includes N decision steps configured in a cascade configuration, each of the N decision steps including one or more stages for analyzing portions of the data.

6. The method of claim 5, wherein the first subset of features are appearance features including a first edge orientation histogram of the first object, and the second subset of features are appearance features including a second edge orientation histogram of the second object.

7. The method of claim 6, further comprising mapping a portion of the data derived from the first and second edge orientation histograms to a scalar value representing a measure of similarity.

8. The method of claim 1, wherein the first signature is a cumulative signature representing a weighted average of single-frame signatures derived from multiple images of the first object, the method further comprising:

updating the first signature of the first object when the second object is an instance of the first object, wherein the second signature is weighted and averaged with the cumulative signature.

9. The method of claim 1, wherein the camera system includes first and second image capturing devices connected to each other in a network, the first and second image capturing devices having, respectively, a first field of view and a second field of view, and the field of view of the camera system corresponding to the first field of view and the second field of view in combination further comprising:

capturing with the second image capturing device the first image of the first object; and

capturing with the first image capturing device the second image of the second object.

10. The method of claim 9, wherein the second image capturing device includes a match classifier for analyzing the data, the method further comprising:

transmitting the second signature from the first image capturing device to the second image capturing device.

11. The method of claim 9, wherein a processor remote from the first and second image capturing devices includes a match classifier for analyzing the data, the method further comprising:

transmitting to the processor the first and second signatures from, respectively, the first and second image capturing devices.

12. The method of claim 1, wherein a training process automatically determines the features of the first and second sets that are to be selected for inclusion in the first and second subsets.

13. The method of claim 1, further comprising searching signatures of a set of objects to identify whether the second object appears in images of the set of objects.

14. The method of claim 13, wherein the searching step comprises:

displaying the second image of the second object on a display;

accepting user input indicative of a selection of the second object;

making determinations as to whether the second signature matches one or more of the signatures of the set of objects; and

sending a notification indicating a match between the second signature and a matching signature of the set of objects.