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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Hadfield, S. Bowden, R. |
| Copyright Year | 2011 |
| Description | Author affiliation: Centre for Vision, Speech and Signal Processing, University of Surrey, Guildford, UK, GU2 7XH (Hadfield, S.; Bowden, R.) |
| Abstract | The motion field of a scene can be used for object segmentation and to provide features for classification tasks like action recognition. Scene flow is the full 3D motion field of the scene, and is more difficult to estimate than it's 2D counterpart, optical flow. Current approaches use a smoothness cost for regularisation, which tends to over-smooth at object boundaries. This paper presents a novel formulation for scene flow estimation, a collection of moving points in 3D space, modelled using a particle filter that supports multiple hypotheses and does not oversmooth the motion field. In addition, this paper is the first to address scene flow estimation, while making use of modern depth sensors and monocular appearance images, rather than traditional multi-viewpoint rigs. The algorithm is applied to an existing scene flow dataset, where it achieves comparable results to approaches utilising multiple views, while taking a fraction of the time. |
| Starting Page | 2290 |
| Ending Page | 2295 |
| File Size | 1227188 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781457711015 |
| ISSN | 15505499 |
| e-ISBN | 9781457711022 |
| DOI | 10.1109/ICCV.2011.6126509 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2011-11-06 |
| Publisher Place | Spain |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Cameras Estimation Optical imaging Three dimensional displays Optical sensors Vectors |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Vision and Pattern Recognition Software |
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