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arxiv: 0909.1608 · v1 · pith:NCMSPOLFnew · submitted 2009-09-09 · 💻 cs.CV

Motion Segmentation by SCC on the Hopkins 155 Database

G. Chen , G. Lerman This is my paper
classification 💻 cs.CV
keywords databasemotionmotionssequencesalgorithmapplyaveragebenchmark
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We apply the Spectral Curvature Clustering (SCC) algorithm to a benchmark database of 155 motion sequences, and show that it outperforms all other state-of-the-art methods. The average misclassification rate by SCC is 1.41% for sequences having two motions and 4.85% for three motions.

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  1. Motion Segmentation Using Locally Affine Atom Voting

    cs.CV 2019-07 unverdicted novelty 5.0

    LAAV segments motion via locally affine feature-set affinities as pre-processing for random voting, claiming higher accuracy and lower cost than pairwise methods.