Motion segmentation by SCC on the Hopkins 155 database

Guangliang Chen, Gilad Lerman

Research output: Chapter in Book/Report/Conference proceedingConference contribution

16 Scopus citations

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 and 4.85% for three motions.

Original languageEnglish (US)
Title of host publication2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops 2009
Pages759-764
Number of pages6
DOIs
StatePublished - 2009
Event2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops 2009 - Kyoto, Japan
Duration: Sep 27 2009Oct 4 2009

Publication series

Name2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops 2009

Other

Other2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops 2009
CountryJapan
CityKyoto
Period9/27/0910/4/09

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