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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Kokkinos, I. Bronstein, M.M. Litman, R. Bronstein, A.M. |
| Copyright Year | 2012 |
| Description | Author affiliation: School of Electrical Engineering, Tel Aviv University, Israel (Litman, R.; Bronstein, A.M.) || Faculty of Informatics, Università della Svizzera Italiana, Lugano, Switzerland (Bronstein, M.M.) || Center for Visual Computing, Ecole Centrale Paris/INRIA Saclay, France (Kokkinos, I.) |
| Abstract | In this work, we present intrinsic shape context (ISC) descriptors for 3D shapes. We generalize to surfaces the polar sampling of the image domain used in shape contexts: for this purpose, we chart the surface by shooting geodesic outwards from the point being analyzed; ‘angle’ is treated as tantamount to geodesic shooting direction, and radius as geodesic distance. To deal with orientation ambiguity, we exploit properties of the Fourier transform. Our charting method is intrinsic, i.e., invariant to isometric shape transformations. The resulting descriptor is a meta-descriptor that can be applied to any photometric or geometric property field defined on the shape, in particular, we can leverage recent developments in intrinsic shape analysis and construct ISC based on state-of-the-art dense shape descriptors such as heat kernel signatures. Our experiments demonstrate a notable improvement in shape matching on standard benchmarks. |
| Starting Page | 159 |
| Ending Page | 166 |
| File Size | 725019 |
| Page Count | 8 |
| File Format | |
| ISBN | 9781467312264 |
| ISSN | 10636919 |
| e-ISBN | 9781467312288 |
| e-ISBN | 9781467312271 |
| DOI | 10.1109/CVPR.2012.6247671 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-06-16 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Shape Context Surface treatment Geometry Heating Kernel Standards |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Vision and Pattern Recognition Software |
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