TY - GEN
T1 - Motion segmentation by SCC on the Hopkins 155 database
AU - Chen, Guangliang
AU - Lerman, Gilad
PY - 2009
Y1 - 2009
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=77953187371&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77953187371&partnerID=8YFLogxK
U2 - 10.1109/ICCVW.2009.5457626
DO - 10.1109/ICCVW.2009.5457626
M3 - Conference contribution
AN - SCOPUS:77953187371
SN - 9781424444427
T3 - 2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops 2009
SP - 759
EP - 764
BT - 2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops 2009
T2 - 2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops 2009
Y2 - 27 September 2009 through 4 October 2009
ER -