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Publikation: Bidrag til tidsskrift › Konferenceartikel › Forskning › fagfællebedømt
We present a novel framework for motion segmentation that combines the concepts of layer-based methods and feature-based motion estimation. We estimate the initial correspondences by comparing vectors of filter outputs at interest points, from which we compute candidate scene relations via random sampling of minimal subsets of correspondences. We achieve a dense, piecewise smooth assignment of pixels to motion layers using a fast approximate graph-cut algorithm based on a Markov random field formulation. We demonstrate our approach on image pairs containing large inter-frame motion and partial occlusion. The approach is efficient and it successfully segments scenes with inter-frame disparities previously beyond the scope of layer-based motion segmentation methods.
Originalsprog | Engelsk |
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Tidsskrift | Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition |
Vol/bind | 1 |
Sider (fra-til) | I/37-I/44 |
ISSN | 1063-6919 |
Status | Udgivet - 2003 |
Eksternt udgivet | Ja |
Begivenhed | 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Madison, WI, USA Varighed: 18 jun. 2003 → 20 jun. 2003 |
Konference
Konference | 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition |
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Land | USA |
By | Madison, WI |
Periode | 18/06/2003 → 20/06/2003 |
Sponsor | IEEE Computer Society TCPAMI |
ID: 302056514