19 June 2017 Multimodal recognition based on face and ear using local feature
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Proceedings Volume 10443, Second International Workshop on Pattern Recognition; 104430K (2017) https://doi.org/10.1117/12.2280343
Event: Second International Workshop on Pattern Recognition, 2017, Singapore, Singapore
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.
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Ruyin Yang, Zhichun Mu, Long Chen, Tingyu Fan, "Multimodal recognition based on face and ear using local feature", Proc. SPIE 10443, Second International Workshop on Pattern Recognition, 104430K (19 June 2017); doi: 10.1117/12.2280343; https://doi.org/10.1117/12.2280343
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