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Real-time Facial Expressions Recognition System for Service Robot based-on ASM and SVMs

机译:基于ASM和SVM的服务机器人实时表情识别系统。

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A real-time facial expressions recognition system is developed for human-robot interaction of service robot. The proposed system is mainly composed of two subsystems: one for Active shape model(ASM) motion extraction, and one for the classification of the estimated motion. The system first uses a cascade classifier to locate the potential face regions from video frame. Then, ASM is automatically initialized in the candidate regions. Based on the statistical property of deformable ASM, some facial features are extracted by using real-time pyramid ASM fitting method. The geometrical displacement between the estimated ASM feature node coordinates and mean shape of ASM is fed into the recognition subsystem in which, a Support Vector Machines (SVMs) is proposed to classify the calculated landmarks’ relative motion. Experimental results show the potential performance of our facial expressions recognition system.
机译:开发了一种用于服务机器人人机交互的实时面部表情识别系统。该系统主要由两个子系统组成:一个子系统用于主动形状模型(ASM)运动提取,另一个子系统用于估计运动的分类。系统首先使用级联分类器从视频帧中定位潜在的面部区域。然后,在候选区域中自动初始化ASM。基于变形ASM的统计特性,采用实时金字塔ASM拟合方法提取了一些面部特征。估计的ASM特征节点坐标和ASM的平均形状之间的几何位移被输入到识别子系统,在该子系统中,提出了一个支持向量机(SVM)对计算出的地标的相对运动进行分类。实验结果表明,我们的面部表情识别系统具有潜在的性能。

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