DocumentCode :
2101500
Title :
Motion analysis: model selection and motion segmentation
Author :
Gheissari, Niloofar ; Bab-Hadiashar, Alireza
Author_Institution :
Sch. of Eng. & Sci., Swinburne Univ. of Technol., Hawthorn, Vic., Australia
fYear :
2003
fDate :
17-19 Sept. 2003
Firstpage :
442
Lastpage :
447
Abstract :
A new model selection criterion based on physical characteristics of underlying motion models is proposed. The proposed criterion is then incorporated in a robust motion segmentation scheme, which is based upon robust least K-th order statistical model fitting. The proposed model criterion has been compared with many other competing techniques and is shown to be more suitable for the motion segmentation task. The motion segmentation algorithm has been tested (and shown to be successful) on a number of synthetic and real image sequences.
Keywords :
computer vision; image motion analysis; image segmentation; image sequences; statistical analysis; computer vision; least K-th order statistical model fitting; model selection; motion analysis; real image sequences; robust motion segmentation; synthetic image sequences; Application software; Computer vision; Image motion analysis; Image sequences; Layout; Motion analysis; Motion segmentation; Pattern recognition; Robustness; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Analysis and Processing, 2003.Proceedings. 12th International Conference on
Print_ISBN :
0-7695-1948-2
Type :
conf
DOI :
10.1109/ICIAP.2003.1234090
Filename :
1234090
Link To Document :
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