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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Guney, F. Geiger, A. |
| Copyright Year | 2015 |
| Description | Author affiliation: MPI, Tubingen, Germany (Guney, F.; Geiger, A.) |
| Abstract | Stereo techniques have witnessed tremendous progress over the last decades, yet some aspects of the problem still remain challenging today. Striking examples are reflecting and textureless surfaces which cannot easily be recovered using traditional local regularizers. In this paper, we therefore propose to regularize over larger distances using object-category specific disparity proposals (displets) which we sample using inverse graphics techniques based on a sparse disparity estimate and a semantic segmentation of the image. The proposed displets encode the fact that objects of certain categories are not arbitrarily shaped but typically exhibit regular structures. We integrate them as non-local regularizer for the challenging object class `car' into a superpixel based CRF framework and demonstrate its benefits on the KITTI stereo evaluation. At time of submission, our approach ranks first across all KITTI stereo leaderboards. |
| Starting Page | 4165 |
| Ending Page | 4175 |
| File Size | 1070560 |
| Page Count | 11 |
| File Format | |
| ISSN | 10636919 |
| e-ISBN | 9781467369640 |
| DOI | 10.1109/CVPR.2015.7299044 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2015-06-07 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Solid modeling Three-dimensional displays Semantics Design automation Mathematical model Proposals Shape |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Vision and Pattern Recognition Software |
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