What went where
Research output: Contribution to journal › Conference article › Research › peer-review
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.
Original language | English |
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Journal | Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition |
Volume | 1 |
Pages (from-to) | I/37-I/44 |
ISSN | 1063-6919 |
Publication status | Published - 2003 |
Externally published | Yes |
Event | 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Madison, WI, United States Duration: 18 Jun 2003 → 20 Jun 2003 |
Conference
Conference | 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition |
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Country | United States |
City | Madison, WI |
Period | 18/06/2003 → 20/06/2003 |
Sponsor | IEEE Computer Society TCPAMI |
ID: 302056514