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