Paper
19 June 2017 Multimodal recognition based on face and ear using local feature
Author Affiliations +
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.
© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ruyin Yang, Zhichun Mu, Long Chen, and 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); https://doi.org/10.1117/12.2280343
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KEYWORDS
Ear

Facial recognition systems

Databases

Image segmentation

Biometrics

Detection and tracking algorithms

Head

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