SYSTEM AND METHOD FOR LOCATING A TARGET WITH A NETWORK OF CAMERAS

• US 20120147191A1
• Filed: 04/19/2010
• Published: 06/14/2012
• Est. Priority Date: 04/17/2009
• Status: Abandoned Application

• Current Assignee: Universite de Technologie de Troyes
• Original Assignee: Universite de Technologie de Troyes
• Inventors: Snoussi, Hichem
• Application Number:
  US13/264,711
• Publication Number:
  US 20120147191A1
• Time in Patent Office: Days
• US Class Current: 348/159
• CPC Class Codes: G06T 2207/10016 Video; Image sequence
• CPC Class Codes: G06T 2207/30232 Surveillance
• CPC Class Codes: G06T 7/277 involving stochastic approaches, e.g. using Kalman filters
• 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: 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 13/19645 Multiple cameras, each having view on one of a plurality of scenes, e.g. multiple cameras for multi-room surveillance or for tracking an object by view hand-over

Abstract

The present invention relates to a system, a method and an intelligent camera for following at least one target (X) with at least one intelligent camera (S) comprising means (S1) for processing data implementing at least one algorithm (AS, AD, AF) for following target(s), means (S2) for acquiring images and means (S21) for communication, characterized in that a detection of at least one target (X) in the region (Z) covered, by virtue of at least one algorithm (AD) for detection at an initial instant, is followed, for each instant (t), by an iteration of at least one step of following the target (X) with at least one camera, termed an active camera, by virtue of at least one variational filtering algorithm (AF) based on a variational filter by estimation (551) of the position of the target (X) through a continuous mixture of Gaussians.

Claims

1. A method for tracking at least one target using a network of intelligent cameras, each comprising data processing resources implementing at least one algorithm for tracking a target or targets, image acquisition resources and communication resources, the network of cameras covering at least one geographic area, called the region, comprising detection of at least one target in the region, by at least one camera in the network, based on execution of at least one detection algorithm, followed by, for each instant (t), an iteration of at least one tracking operation of the target by at least one camera, called the active camera, thanks to at least one variational filtering algorithm based on a variational filter, using a likelihood function for the position of the target in the image acquired by said active camera and using a model, called a transition model, represented by a continuous mixture of Gaussians and based on a temporal correlation of a trajectory of the target from one instant to another, by implementing estimation of the position of the target by a probability density.

2. A method according to claim 1, wherein the tracking operation at a given instant (t), further comprises a determination of data representative of a sufficient statistic in temporal terms, representing knowledge of the trajectory, for continuing the tracking of the target in the following instant (t+1).

3. A method according to claim 1, wherein the tracking operation at a given instant (t), further comprises a determination of a relevance indicator of the estimate of the position of the target, based on execution of at least one selection algorithm allowing the selection of at least one active camera for performing tracking, according on its relevance indicator which represents the difference between the probability density of the target'"'"'s position predicted in the previous instant and the probability density of the target'"'"'s position estimated in the current instant.

4. A method according to claim 3, wherein the detection of at least one target present in the region at an initial instant, triggers the tracking of the target by all cameras having detected the target, followed by a competition between the cameras according to the determined relevance indicator, for selecting the most relevant and assembling a set of cameras, called active cameras, assigned to tracking at the given instant (t).

5. A method according to claim 3, wherein the determination of a relevance indicator of the processing performed triggers a comparison for each camera active at a given instant (t), of the relevance indicator with a threshold determined in the selection algorithm allowing the camera, depending on the result of the comparison, to continue tracking or to stop tracking.

6. A method according to claim 5, wherein the comparison for each camera active at a given instant (t), of its relevance indicator with a threshold is accompanied by a comparison of the change in the relevance indicators of the other cameras, to take that change into account in deciding between continuing tracking and giving it up stopping tracking, and deciding whether to transmit to other cameras in the network its data representative of the sufficient statistic determined by that camera, this transmission triggering the reiteration of the competition between the cameras for assembling a new set when the relevance indicator of all the cameras crosses the threshold.

7. A method according to claim 1, characterized in that the tracking operation comprises, at each instant (t), an iteration of a prediction of the position(s) of the target(s) in the following instant.

8. A method according to claim 1, wherein the data (SS) representative of sufficient statistics in temporal terms are representative of a mean and a covariance of the random mean of the estimated position of the target.

9. A method according to claim 1, wherein the cameras have known geographic locations based on the processing resources use of data representative of the relative positioning of their respective fields of vision.

10. A method according to claim 9, wherein the tracking step, using variational filtering, at the instant (t), when several cameras are activated, is implemented in a collaborative manner by the active cameras, based on a dependence between their respective variational filters expressed by a dynamic homography model connection the random resources of the position of the target estimated respectively by each of the active cameras.

11. A method according to claim 10, wherein tracking is performed collaboratively by the active cameras by exchanging data representative of sufficient statistics in spatial terms between cameras, in addition to those in temporal terms, these sufficient statistics in spatial terms representing the likelihood factors of the positions of the target in the image of each camera active at the current instant (t).

12. A system for tracking at least one target by a network of intelligent cameras, each comprising data processing resources, image acquisition resources and communication resources, the network of cameras covering at least one geographic area, called the region, wherein the data processing resources implement at least one algorithm for locating and tracking target(s) by implementing the method according to claim 1.

13. A system according to claim 12, wherein at least one algorithm used is based on a variational filter allowing the data exchanged between the cameras for tracking to be limited to one mean and one covariance.

14. A system according to claim 12, wherein at least one image is able to be acquired during tracking by at least one of the cameras, selected according to its position with respect to the coordinates and/or to the trajectory of the target.

15. A system according to claim 14, wherein said image, acquired by at least one camera selected for its position, is stored in the memory resources of the same camera.

16. A system according to 12, further comprising at least one centralization device comprising memory means and/or display resources for, respectively, storage and/or display of data relating to tracking and/or to said acquired image, transmitted by the cameras.

17. A system according to claim 16, wherein the centralization device further comprises input resources allowing an operator to check tracking of the target based on data transmitted by the cameras and displayed on said device and, if applicable, to alert a cognizant office via the communication resources of said device.

18. An intelligent camera, covering at least one geographic area and comprising data processing resources, image acquisition resources, wherein the data processing resources implement at least one algorithm for locating a target or targets by implementing the method according to claim 1.

19. An intelligent camera according to the foregoing claim, further comprising communication resources for communicating with another intelligent camera for implementing the method according to claim 1.

20. An intelligent camera according to 18, further comprising communication resources for communicating with a centralization device comprising resources of communicating with at least one camera and memory resources and/or display resources for respectively storing and/or displaying data relating to tracking and/or to said acquired image.