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Proceedings Paper

Multimodal recognition based on face and ear using local feature
Author(s): Ruyin Yang; Zhichun Mu; Long Chen; Tingyu Fan
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Paper Abstract

The pose issue which may cause loss of useful information has always been a bottleneck in face and ear recognition. To address this problem, we propose a multimodal recognition approach based on face and ear using local feature, which is robust to large facial pose variations in the unconstrained scene. Deep learning method is used for facial pose estimation, and the method of a well-trained Faster R-CNN is used to detect and segment the region of face and ear. Then we propose a weighted region-based recognition method to deal with the local feature. The proposed method has achieved state-of-the-art recognition performance especially when the images are affected by pose variations and random occlusion in unconstrained scene.

Paper Details

Date Published: 19 June 2017
PDF: 7 pages
Proc. SPIE 10443, Second International Workshop on Pattern Recognition, 104430K (19 June 2017); doi: 10.1117/12.2280343
Show Author Affiliations
Ruyin Yang, Univ. of Science and Technology Beijing (China)
Zhichun Mu, Univ. of Science and Technology Beijing (China)
Long Chen, Univ. of Science and Technology Beijing (China)
Tingyu Fan, Univ. of Science and Technology Beijing (China)


Published in SPIE Proceedings Vol. 10443:
Second International Workshop on Pattern Recognition
Xudong Jiang; Masayuki Arai; Guojian Chen, Editor(s)

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