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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Tabia, H. Ngoc-Son Vu |
| Copyright Year | 2014 |
| Description | Author affiliation: ETIS/ENSEA, Univ. of Cergy-Pontoise, Cergy-Pontoise, France (Tabia, H.; Ngoc-Son Vu) |
| Abstract | The intent of 3D-model classification is to find categories of similar objects according to their shapes. This task is a challenging and important problem in 3D-mining and shape processing. In this paper, we present a novel method to categorize 3D-objects based on view-based descriptors. The proposed method goes into two stages. The first stage corresponds to the training in which 3D-objects in the same category are processed and a set of representative 2D views is selected, The second stage corresponds to the labelling in which unknown objects are classified using a belief based classifier. The experimental results obtained on the Shrec07 datasets show that the system efficiently performs in categorizing 3D-models. |
| Starting Page | 297 |
| Ending Page | 302 |
| File Size | 538391 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781479952090 |
| ISSN | 10514651 |
| DOI | 10.1109/ICPR.2014.60 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2014-08-24 |
| Publisher Place | Sweden |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Three-dimensional displays Shape Training Clustering algorithms Labeling Accuracy Feature extraction |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Vision and Pattern Recognition |
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