3D Model Retrieval Based on Representative Views
3D model retrieval based on representative views was proposed. On the view representation of the 3D model, in order to fully represent the model and reduce redundant information, we firstly adopt Light Field Descriptor (LFD) to generate 2D views, and then use K-MEANS to get representative views from...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Harbin University of Science and Technology Publications
2021-12-01
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| Series: | Journal of Harbin University of Science and Technology |
| Subjects: | |
| Online Access: | https://hlgxb.hrbust.edu.cn/#/digest?ArticleID=2030 |
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| Summary: | 3D model retrieval based on representative views was proposed. On the view representation of the 3D model, in order to fully represent the model and reduce redundant information, we firstly adopt Light Field Descriptor (LFD) to generate 2D views, and then use K-MEANS to get representative views from the 2D views. Next, a Convolution Neural Network (CNN) is adopted to extract the view feature and classify. At the same time, a similarity metrics supporting multiple query method is proposed to realize model retrieval with sketches, pictures or 3D models as input. Results on ModelNet40 showed that the proposed method could achieve an accuracy of 100% for part of models with distinct features |
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| ISSN: | 1007-2683 |