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首页> 外文会议>Humaine Association Conference on Affective Computing and Intelligent Interaction >Local Gabor Binary Patterns from Three Orthogonal Planes for Automatic Facial Expression Recognition
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Local Gabor Binary Patterns from Three Orthogonal Planes for Automatic Facial Expression Recognition

机译：来自三个正交平面的本地Gabor二进制模式，用于自动面部表情识别

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摘要

Facial actions cause local appearance changes over time, and thus dynamic texture descriptors should inherently be more suitable for facial action detection than their static variants. In this paper we propose the novel dynamic appearance descriptor Local Gabor Binary Patterns from Three Orthogonal Planes (LGBP-TOP), combining the previous success of LGBP-based expression recognition with TOP extensions of other descriptors. LGBP-TOP combines spatial and dynamic texture analysis with Gabor filtering to achieve unprecedented levels of recognition accuracy in real-time. While TOP features risk being sensitive to misalignment of consecutive face images, a rigorous analysis of the descriptor shows the relative robustness of LGBP-TOP to face registration errors caused by errors in rotational alignment. Experiments on the MMI Facial Expression and Cohn-Kanade databases show that for the problem of FACS Action Unit detection, LGBP-TOP outperforms both its static variant LGBP and the related dynamic appearance descriptor LBP-TOP.
机译：面部措施导致局部外观随时间变化，因此动态纹理描述符应该通常更适合于面部动作检测，而不是其静态变体。在本文中，我们提出了来自三个正交平面（LGBP-TOP）的新型动态外观描述符本地Gabor二进制模式，与其他描述符的顶部扩展相结合了基于LGBP的表达式的先前成功。 LGBP-TOP将空间和动态纹理分析与Gabor滤波相结合，实时实现了前所未有的识别准确度。虽然顶部特征风险对连续面部图像的未对准敏感，但对描述符的严格分析表明LGBP-TOP对旋转对准中的误差引起的面部登记误差的相对稳健性。 MMI面部表情和Cohn-Kanade数据库的实验表明，对于FACS动作单元检测的问题，LGBP-Top优于其静态变体LGBP和相关动态外观描述符LBP-Top。

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