The key challenge is estimating the segment boundaries of (partially) occluded objects, which areinherently ambiguous when considering only a single frame . We propose Multihypothesis Segmentation Tracking (MST), a novel method forvolumetric segmentation in changing scenes . MST outperforms baselines in all tested scenes, showing it outperforms baselines in all tests . These methods allow MST to track the segmentation state over time and incorporate new information, such as new objects being revealed . We evaluateour method on several cluttered tabletop environments in simulation and reality. Our results show that MST performs well in all tests of MST in simulated and reality-based environments. We evaluate

Author(s) : Andrew Price, Kun Huang, Dmitry Berenson

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Code :
Coursera

Keywords : mst - segmentation - tracking - environments - baselines -

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