DocumentCode
2387720
Title
Two clustering algorithms and their application to motion segmentation
Author
Trajkovic, Miroslav ; Hedley, Mark
Author_Institution
Dept. of Electr. Eng., Sydney Univ., NSW, Australia
Volume
2
fYear
1996
fDate
26-29 Nov 1996
Firstpage
939
Abstract
Two clustering algorithms have been developed for data classification where there exists no a priori knowledge about the number of clusters. One algorithm is based on robust statistics, while the another one was motivated by the N body problem of theoretical mechanics. The algorithms were applied to the problem of motion segmentation of image sequences, based on similarity in velocity space. Experimental results for the two algorithms are presented and compared
Keywords
image classification; image sequences; mechanics; motion estimation; statistical analysis; N body problem; clustering algorithms; data classification; experimental results; image sequences; motion segmentation; robust statistics; theoretical mechanics; velocity space similarity; Clustering algorithms; Computer vision; Detectors; Image sequences; Layout; Motion segmentation; Optical computing; Partitioning algorithms; Robustness; Statistics;
fLanguage
English
Publisher
ieee
Conference_Titel
TENCON '96. Proceedings., 1996 IEEE TENCON. Digital Signal Processing Applications
Conference_Location
Perth, WA
Print_ISBN
0-7803-3679-8
Type
conf
DOI
10.1109/TENCON.1996.608474
Filename
608474
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