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
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;
Conference_Titel :
TENCON '96. Proceedings., 1996 IEEE TENCON. Digital Signal Processing Applications
Conference_Location :
Perth, WA
Print_ISBN :
0-7803-3679-8
DOI :
10.1109/TENCON.1996.608474
