Method for automatic detection and tracking of multiple targets with multiple cameras and system therefor
First Claim
1. A method of detecting and tracking multiple targets within a surveillance zone with multiple cameras, comprising the steps of:
- (a) analyzing a detection result of a plurality of camera views using a target detection algorithm to generate a plurality of analysis data;
(b) integrating the analysis data with a Baysian framework to create a target detection probability (TDP) distribution; and
(c) simultaneously and automatically detecting and tracking a plurality of moving targets in the camera views within the surveillance zone,wherein the surveillance zone is determined by overlapping fields of view of all of the multiple cameras, andwherein the TDP distribution in the step (b) equals to a sum of a probability, G1(X), making a newly appearing target to be detected easily and a probability, G2(X), providing temporal information in the time domain between successive frames, and X is a location on a ground plane.
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Abstract
A method for automatically detecting and tracking multiple targets in a multi-camera surveillance zone and system thereof. In each camera view of the system only a simple object detection algorithm is needed. The detection results from multiple cameras are fused into a posterior distribution, named TDP, based on the Bayesian rule. This TDP distribution represents a likelihood of presence of some moving targets on the ground plane. To properly handle the tracking of multiple moving targets with time, a sample-based framework which combines Markov Chain Monte Carlo (MCMC), Sequential Monte Carlo (SMC), and Mean-Shift Clustering, is provided. The detection and tracking accuracy is evaluated by both synthesized videos and real videos. The experimental results show that this method and system can accurately track a varying number of targets.
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Citations
5 Claims
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1. A method of detecting and tracking multiple targets within a surveillance zone with multiple cameras, comprising the steps of:
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(a) analyzing a detection result of a plurality of camera views using a target detection algorithm to generate a plurality of analysis data; (b) integrating the analysis data with a Baysian framework to create a target detection probability (TDP) distribution; and (c) simultaneously and automatically detecting and tracking a plurality of moving targets in the camera views within the surveillance zone, wherein the surveillance zone is determined by overlapping fields of view of all of the multiple cameras, and wherein the TDP distribution in the step (b) equals to a sum of a probability, G1(X), making a newly appearing target to be detected easily and a probability, G2(X), providing temporal information in the time domain between successive frames, and X is a location on a ground plane. - View Dependent Claims (2, 3, 4, 5)
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Specification