Transform invariant based motion segmentation

Yufeng Chen; Fengxia Li; Peng Lu

doi:10.1117/12.833496

30 October 2009 Transform invariant based motion segmentation

Yufeng Chen, Fengxia Li, Peng Lu

Proceedings Volume 7495, MIPPR 2009: Automatic Target Recognition and Image Analysis; 749526 (2009) https://doi.org/10.1117/12.833496
Event: Sixth International Symposium on Multispectral Image Processing and Pattern Recognition, 2009, Yichang, China

Abstract

Motion segmentation is being paid more and more attention in computer vision with the rapid increasing requirement of content based coding, motion based recognition and etc. However, the robustness and efficiency of motion segmentation is still a challenging problem. In this paper we propose a novel motion segmentation method, which is based on the transform invariant of local motion, to try to segment motion features in an efficient way. Generally a complex motion can be viewed as a combination of local rigid motion, a certain kind of relationships between features in the same rigid parts remain the same under arbitrary transform. Once a number of feature points are considered as the same motion parts by the invariants, the transform parameters of the motion can be retrieved. To consider the motion segmentation globally, the motion segmentation process can be refined and their corresponding feature point set can be segmented. Experiments have been implemented to segment human body parts and show the effectiveness of the computation and satisfaction of the results compared with traditional methods.

Citation Download Citation

Yufeng Chen, Fengxia Li, and Peng Lu "Transform invariant based motion segmentation", Proc. SPIE 7495, MIPPR 2009: Automatic Target Recognition and Image Analysis, 749526 (30 October 2009); https://doi.org/10.1117/12.833496

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KEYWORDS

Image segmentation

Feature extraction

Motion analysis

Motion models

Motion detection

Optical flow

Computer vision technology

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