Region-based affine motion segmentation using color information

This paper presents region-based affine motion parameter clustering methods by motion-vector and intensity matching to provide improved robustness and alignment of motion boundaries with real object boundaries. Regions may be formed as fixed- or variable-size rectangular blocks, triangular patches,...

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Bibliographic Details
Main Authors: Eren, P.E., Altunbasak, Y., Tekalp, A.M.
Format: Conference Proceeding
Language:English
Subjects:
Applied sciences
Bayesian methods
Clustering methods
Computer vision
Deformable models
Estimation error
Exact sciences and technology
Image processing
Image segmentation
Image sequences
Information, signal and communications theory
Motion estimation
Motion segmentation
Robustness
Signal processing
Telecommunications and information theory
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Description
Summary:This paper presents region-based affine motion parameter clustering methods by motion-vector and intensity matching to provide improved robustness and alignment of motion boundaries with real object boundaries. Regions may be formed as fixed- or variable-size rectangular blocks, triangular patches, or arbitrary-shaped areas defined by color or texture uniformity. A particular combination of these affine clustering methods is then proposed to obtain the best segmentation results on a variety of image sequences. Experimental results showing the benefits of the proposed scheme are provided.
ISSN:1520-6149
2379-190X
DOI:10.1109/ICASSP.1997.595424