Target Detection and Tracking for Video Surveillance

Abstract

Target detection and tracking is an important problem in the automatic surveillance system. This paper proposes a Combined Gaussian Hidden Markov Model based Kalman Filter (CGHMM-KF) scheme for tracking people in multiple camera sensor network for monitoring and tracking of target (person/vehicle) in secured area. To detect the target under different illumination conditions, HMM with Mixture of Gaussians (MoG) is adapted. The MoG estimates the background and detects the foreground and the HMM modeling technique captures the shape of the desired object from the foreground. Finally, tracking of multiple targets is done by Kalman Filter (KF) with a bounding box, indicating the location of the person even with the motion in the background. The area of coverage can be extended dynamically using multiple cameras. The proposed approach provides better detection and tracking of person even in the presence of occlusion, target miss association and multiple persons in the environment.