Learning Stacked Image Descriptor for Face Recognition
Learning Stacked Image Descriptor for Face Recognition
复制标题
学习用于人脸识别的堆叠图像描述符
DOI:
10.1109/tcsvt.2015.2473415
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发表时间:
2016-09
期刊:
影响因子:
--
通讯作者:
Stan Z. Li
中科院分区:
文献类型:
--
作者:
Zhen Lei;Dong Yi;Stan Z. Li
Learning-based face descriptors have constantly improved the face recognition performance. Compared with the hand-crafted features, learning-based features are considered to be able to exploit information with better discriminative ability for specific tasks. Motivated by the recent success of deep learning, in this paper, we extend the original shallow face descriptors to deep discriminant face features by introducing a stacked image descriptor (SID). With deep structure, more complex facial information can be extracted and the discriminant and compactness of feature representation can be improved. The SID is learned in a forward optimization way, which is computational efficient compared with deep learning. Extensive experiments on various face databases are conducted to show that SID is able to achieve high face recognition performance with compact face representation, compared with other state-of-the-art descriptors.
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DOI:
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发表时间:
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期刊:
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影响因子:
--
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发表时间:
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影响因子:
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