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A real time implementation of a pose invariant face recognition engine with a novel face segmentation algorithm

机译:一种具有新颖人脸分割算法的姿势不变人脸识别引擎的实时实现

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In this paper we propose a fast and efficient algorithm for segmenting a face suitable for recognition from a video sequence. We first obtain a coarse face region using skin color, then using dynamic template matching the face is efficiently segmented at varying scale and pose in real time. We have also developed and tested some heuristics which localizes only the face region, even when subjects are wearing skin color dress. The segmented face is then handed over to a recognition algorithm based on principal component analysis and linear discriminant analysis. The on-line face detection, segmentation and recognition algorithm takes an average of 0.06 sec on a 3.2 GHz P4 machine.
机译:在本文中,我们提出了一种快速有效的算法,用于分割适合从视频序列识别的人脸。我们首先使用肤色获得一个粗糙的面部区域,然后使用匹配的动态模板对面部进行实时有效地以可变比例和姿势分割。我们还开发并测试了一些启发式方法,即使在受试者穿着肤色衣服时,这些启发式方法也只能定位脸部区域。然后将分割后的脸部切换到基于主成分分析和线性判别分析的识别算法。在3.2 GHz P4机器上,在线人脸检测,分割和识别算法平均需要0.06秒。

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