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MoT - Mixture of Trees Probabilistic Graphical Model for Video Segmentation
This video was recorded at British Machine Vision Conference (BMVC), Surrey 2012. We present a novel mixture of trees (MoT) graphical model for video segmentation. Each component in this mixture represents a tree structured temporal linkage between super-pixels from the first to the last frame of a video sequence. Our time-series model explicitly captures the uncertainty in temporal linkage between adjacent frames which improves segmentation accuracy. We provide a variational inference scheme for this model to estimate super-pixel labels and their confidences in nearly realtime. The efficacy of our approach is demonstrated via quantitative comparisons on the challenging SegTrack joint segmentation and tracking dataset.
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This work is licensed under a Attribution-NonCommercial-NoDerivs 3.0 United States
