Interactive Tracking of 2D Generic Objects with Spacetime Optimization
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
Joint trajectory tracking and recognition based on bi-directional nonlinear learning
Image and Vision Computing
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
Mean Shift tracking with multiple reference color histograms
Computer Vision and Image Understanding
Analytical dynamic programming tracker
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part I
International Journal of Computer Vision
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In this paper, we present a novel approach to keyframe-based tracking, called bi-directional tracking. Given two object templates in the beginning and ending keyframes, the bi-directional tracker outputs the MAP (Maximum A Posterior) solution of the whole state sequence of the target object in the Bayesian framework. First, a number of 3D trajectory segments of the object are extracted from the input video, using a novel trajectory segment analysis. Second, these disconnected trajectory segments due to occlusion are linked by a number of inferred occlusion segments. Last, the MAP solution is obtained by trajectory optimization in a coarse-to-fine manner. Experimental results show the robustness of our approach with respect to sudden motion, ambiguity, and short and long periods of occlusion.