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Robust Realtime Motion-Split-And-Merge for Motion Segmentation

Ralf Dragon, Jörn Ostermann, Luc Van Gool


In this paper, we analyze and modify the Motion-Split-and-Merge (MSAM) algorithm for the motion segmentation of correspondences between two frames. Our goal is to make the algorithm suitable for practical use which means realtime processing speed at very low error rates. We compare our (robust realtime) RMSAM with J-Linkage and Graph-Based Segmentation and show that it is superior to both. Applying RMSAM in a multi-frame motion segmentation context in the Hopkins 155 benchmark, we show that compared to the original formulation, the runtime is reduced by 72%, and the error by 68% to only 0.65%. This is in the magnitude of the best results reported so far, but RMSAM additionally allows realtime segmentation, and it can handle outliers and unconstrained missing data.

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  author = {Ralf Dragon and J\"orn Ostermann and Luc Van Gool},
  title = {Robust Realtime Motion-Split-And-Merge for Motion Segmentation},
  booktitle = {GCPR (DAGM)},
  year = {2013},
  keywords = {}