A Modular Approach and Voting Scheme on 3D Face Recognition
In this paper, we carried out a modular approach human 3D face recognition across neutral and six basic facial expressions experiments. Initially, a face model is decomposed into several modules before the 3D facial points for each of the modules are extracted. Three sizes of modules are used in ou...
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| Main Authors: | , , |
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| Format: | Proceeding |
| Language: | en |
| Published: |
2015
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| Subjects: | |
| Online Access: | http://ir.unimas.my/id/eprint/39748/1/A%20Modular%20Approach%20and%20Voting%20Scheme.pdf http://ir.unimas.my/id/eprint/39748/ https://ieeexplore.ieee.org/document/7024451 |
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| Summary: | In this paper, we carried out a modular approach
human 3D face recognition across neutral and six basic facial expressions experiments. Initially, a face model is decomposed into several modules before the 3D facial points for each of the modules are extracted. Three sizes of modules are used in our experiments: 2-Module, 6-Module and 10-Module. We apply Support Vector Machines as the classifier to each of the modules. A Majority Voting Scheme (MVS) and Weighted Voting Scheme (WVS) are constructed to infer the emotion underlying a collection of modules. From the analysis, we conclude that 10-Module outperforms 2-Module and 6-Module. In addition, the modules with low amount feature vectors and only contain boundary feature vectors perform worst. |
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