Cube of Space Sampling for 3D Model Retrieval
Since the number of 3D models is rapidly increasing, extracting better feature descriptors to represent 3D models is very challenging for effective 3D model retrieval. There are some problems in existing 3D model representation approaches. For example, many of them focus on the direct extraction of...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-11-01
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| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/11/23/11142 |
| _version_ | 1797508176986243072 |
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| author | Zong-Yao Chen Chih-Fong Tsai Wei-Chao Lin |
| author_facet | Zong-Yao Chen Chih-Fong Tsai Wei-Chao Lin |
| author_sort | Zong-Yao Chen |
| collection | DOAJ |
| description | Since the number of 3D models is rapidly increasing, extracting better feature descriptors to represent 3D models is very challenging for effective 3D model retrieval. There are some problems in existing 3D model representation approaches. For example, many of them focus on the direct extraction of features or transforming 3D models into 2D images for feature extraction, which cannot effectively represent 3D models. In this paper, we propose a novel 3D model feature representation method that is a kind of voxelization method. It is based on the space-based concept, namely CSS (Cube of Space Sampling). The CSS method uses cube space 3D model sampling to extract global and local features of 3D models. The experiments using the ESB dataset show that the proposed method to extract the voxel-based features can provide better classification accuracy than SVM and comparable retrieval results using the state-of-the-art 3D model feature representation method. |
| first_indexed | 2024-03-10T04:58:35Z |
| format | Article |
| id | doaj.art-d1a3da0880ab44a283e979791fcbfb56 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T04:58:35Z |
| publishDate | 2021-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-d1a3da0880ab44a283e979791fcbfb562023-11-23T02:03:14ZengMDPI AGApplied Sciences2076-34172021-11-0111231114210.3390/app112311142Cube of Space Sampling for 3D Model RetrievalZong-Yao Chen0Chih-Fong Tsai1Wei-Chao Lin2Department of Information Management, National Central University, Taoyuan 320317, TaiwanDepartment of Information Management, National Central University, Taoyuan 320317, TaiwanDepartment of Information Management, Chang Gung University, Taoyuan 33302, TaiwanSince the number of 3D models is rapidly increasing, extracting better feature descriptors to represent 3D models is very challenging for effective 3D model retrieval. There are some problems in existing 3D model representation approaches. For example, many of them focus on the direct extraction of features or transforming 3D models into 2D images for feature extraction, which cannot effectively represent 3D models. In this paper, we propose a novel 3D model feature representation method that is a kind of voxelization method. It is based on the space-based concept, namely CSS (Cube of Space Sampling). The CSS method uses cube space 3D model sampling to extract global and local features of 3D models. The experiments using the ESB dataset show that the proposed method to extract the voxel-based features can provide better classification accuracy than SVM and comparable retrieval results using the state-of-the-art 3D model feature representation method.https://www.mdpi.com/2076-3417/11/23/111423D model3D objectcontent-based retrievalre-samplingcollision detectionsimilarity match |
| spellingShingle | Zong-Yao Chen Chih-Fong Tsai Wei-Chao Lin Cube of Space Sampling for 3D Model Retrieval Applied Sciences 3D model 3D object content-based retrieval re-sampling collision detection similarity match |
| title | Cube of Space Sampling for 3D Model Retrieval |
| title_full | Cube of Space Sampling for 3D Model Retrieval |
| title_fullStr | Cube of Space Sampling for 3D Model Retrieval |
| title_full_unstemmed | Cube of Space Sampling for 3D Model Retrieval |
| title_short | Cube of Space Sampling for 3D Model Retrieval |
| title_sort | cube of space sampling for 3d model retrieval |
| topic | 3D model 3D object content-based retrieval re-sampling collision detection similarity match |
| url | https://www.mdpi.com/2076-3417/11/23/11142 |
| work_keys_str_mv | AT zongyaochen cubeofspacesamplingfor3dmodelretrieval AT chihfongtsai cubeofspacesamplingfor3dmodelretrieval AT weichaolin cubeofspacesamplingfor3dmodelretrieval |