ML Anthology

Motion Segmentation by SCC on the Hopkins 155 Database

Guangliang Chen, Gilad Lerman
ICCVW 2009 pp. 759-764
doi:10.1109/ICCVW.2009.5457626 /iccvw/2009/chen2009iccvw-motion/

Abstract

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 and4.85% for three motions.

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Cite

Text

Chen and Lerman. "Motion Segmentation by SCC on the Hopkins 155 Database." IEEE/CVF International Conference on Computer Vision Workshops, 2009. doi:10.1109/ICCVW.2009.5457626

Markdown

[Chen and Lerman. "Motion Segmentation by SCC on the Hopkins 155 Database." IEEE/CVF International Conference on Computer Vision Workshops, 2009.](https://mlanthology.org/iccvw/2009/chen2009iccvw-motion/) doi:10.1109/ICCVW.2009.5457626

BibTeX

@inproceedings{chen2009iccvw-motion,
  title     = {{Motion Segmentation by SCC on the Hopkins 155 Database}},
  author    = {Chen, Guangliang and Lerman, Gilad},
  booktitle = {IEEE/CVF International Conference on Computer Vision Workshops},
  year      = {2009},
  pages     = {759-764},
  doi       = {10.1109/ICCVW.2009.5457626},
  url       = {https://mlanthology.org/iccvw/2009/chen2009iccvw-motion/}
}