A New Hierarchical Particle Filter Based Tracking System for Soccer Game Analysis
PCM '08 Proceedings of the 9th Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
Exemplar-based video inpainting without ghost shadow artifacts by maintaining temporal continuity
IEEE Transactions on Circuits and Systems for Video Technology
On the optimality of motion-based particle filtering
IEEE Transactions on Circuits and Systems for Video Technology
Correspondence propagation with weak priors
IEEE Transactions on Image Processing
Experimental Assessment of Probabilistic Integrated Object Recognition and Tracking Methods
CIARP '09 Proceedings of the 14th Iberoamerican Conference on Pattern Recognition: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
Pose estimation from multiple cameras based on Sylvester's equation
Computer Vision and Image Understanding
Video narrative authoring with motion inpainting
Proceedings of the 1st ACM international workshop on Multimodal pervasive video analysis
Combined feature evaluation for adaptive visual object tracking
Computer Vision and Image Understanding
Fast image motion segmentation for surveillance applications
Image and Vision Computing
Robust visual tracking based on occlusion detection and particle redistribution
ICIMCS '10 Proceedings of the Second International Conference on Internet Multimedia Computing and Service
Computers & Mathematics with Applications
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We propose a fast object tracking algorithm that predicts the object contour using motion vector information. The segmentation step common in region-based tracking methods is avoided, except for the initialization of the object. Tracking is achieved by predicting the object boundary using block motion vectors followed by updating the contour using occlusions/disocclusion detection. An adaptive block-based approach has been used for estimating motion between frames. An efficient modulation scheme is used to control the gap between frames used for motion estimation. The algorithm for detecting disocclusion proceeds in two steps. First, uncovered regions are estimated from the displaced frame difference. These uncovered regions are classified into actual disocclusions and false alarms by observing the motion characteristics of uncovered regions. Occlusion and disocclusion are considered as dual events and this relationship is explained in detail. The algorithm for detecting occlusion is developed by modifying the disocclusion detection algorithm in accordance with the duality principle. The overall tracking algorithm is computationally superior to existing region-based methods for object tracking. The immediate applications of the proposed tracking algorithm are video compression using MPEG-4 and content retrieval based on standards like H.264. Preliminary simulation results demonstrate the performance of the proposed algorithm.