Behavioural analysis with movement cluster model for concurrent actions
Journal on Image and Video Processing - Special issue on advanced video-based surveillance
Simultaneous partitioned sampling for articulated object tracking
ACIVS'11 Proceedings of the 13th international conference on Advanced concepts for intelligent vision systems
Editors Choice Article: Tracking highly correlated targets through statistical multiplexing
Image and Vision Computing
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In this paper, we present two new articulated motion analysis and object tracking approaches: the decentralized articulated object tracking method and the hierarchical articulated object tracking method. The first approach avoids the common practice of using a high-dimensional joint state representation for articulated object tracking. Instead, we introduce a decentralized scheme and model the interpart interaction within an innovative Bayesian framework. Specifically, we estimate the interaction density by an efficient decomposed interpart interaction model. To handle severe self-occlusions, we further extend the first approach by modeling high-level interunit interaction and develop the second algorithm within a consistent hierarchical framework. Preliminary experimental results have demonstrated the superior performance of the proposed approaches on real-world videos in both robustness and speed compared with other articulated object tracking methods.