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Expression Invariant Face Recognition Using Biologically Inspired Features from Visual Cortex Mechanism

机译:利用视觉皮层机制的生物启发特征进行表情不变的人脸识别

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摘要

Face recognition performance has always been influenced by the various facial expressions a subject may achieve. In this paper, we investigate face as a biometric under expression variation using Biologically Inspired Features (BIFs). We apply biologically inspired features, derived from a feed forward model of object recognition pathway in visual cortex for expression invariant face recognition problem. In this work, our goal is to understand whether features motivated by a model of visual cortex are robust for human identification under expression variation. Experimental results show that the model achieves high recognition percentage even for large expression variations.
机译:面部识别性能一直受对象可能达到的各种面部表情的影响。在本文中,我们使用生物启发特征(BIF)研究表情变化下人脸的生物特征。我们应用生物学启发的功能,从视觉皮层中的对象识别路径的前馈模型派生出表达不变的面部识别问题。在这项工作中,我们的目标是了解视觉皮层模型所激发的特征是否对表达变化下的人类识别具有鲁棒性。实验结果表明,即使对于较大的表达差异,该模型也能实现较高的识别率。

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