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Titlebook: Biometric Recognition; 11th Chinese Confere Zhisheng You,Jie Zhou,Qijun Zhao Conference proceedings 2016 Springer International Publishing

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Binary Classifiers and Radial Symmetry Transform for Fast and Accurate Eye Localization is employed to identify the real eyes from the reliable eye candidates. A large number of tests have been completed to verify the performance of the proposed algorithm. Experimental results demonstrate that the algorithm proposed in this article is robust and efficient.
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Extended Robust Cascaded Pose Regression for Face Alignment-level boosted regression are applied to establish accurate relation between features and shapes. Experiments on two challenging face datasets (LFPW, COFW) show that our proposed approach significantly outperforms the state-of-art in terms of both efficiency and accuracy.
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0302-9743 iometrics; Affective Computing; Feature Extraction and Classification Theory; Anti-Spoofing and Privacy; Surveillance; and DNA and Emerging Biometrics..978-3-319-46653-8978-3-319-46654-5Series ISSN 0302-9743 Series E-ISSN 1611-3349
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Muhammad Hasan Amara,Abd Al-Rahman Mar’Imprehensive set of candidate regions. In the latter, we further decide whether the regions are faces using a well-trained Faster R-CNN. Experiments are conducted on the WIDER FACE benchmark, and the results clearly prove the competency of the proposed method at detecting occluded faces.
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https://doi.org/10.1007/978-3-030-74958-3cted by an effective post-processing method. We evaluate the proposed method by performing semi-supervised classification experiments on ORL, Extended Yale B and AR face database. The experimental results show that our approach improves the accuracy of semi-supervised learning and achieves the state-of-the-art performance.
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