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基于模板匹配的人体日常行为识别
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Recognition of Human Daily Action Based on Template Matching
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    提出了一种以运动人体的轮廓为特征,基于模板匹配的人体行为识别方法.利用背景差分法和阴影消除技术从图像中提取完整的人体轮廓.定义一种新的轮廓描述方法,将时变的2D轮廓形状转换为对应的1D距离向量.先计算轮廓点的质心坐标,再将轮廓等弧长地分割,用直线段连接相邻的割点构成对轮廓线的多边形近似,用多边形的顶点到轮廓质心的距离和其两个后继顶点的距离构成的3个距离串来描述轮廓.计算轮廓之间的动态时间规整(DTW)距离,然后利用谱系聚类方法提取行为序列的关键姿态,将关键姿态编码为行为字符串.最后利用编辑距离度量测试序列与标准序列之间的相似性.实验结果表明,利用本方法对人的6种日常行为进行识别,正确识别率达到85.7%以上.

    Abstract:

    A template matchbased method was presented by using the contours of image sequence as representative descriptors of human posture to achieve human action recognition. First, the entire binary image of human silhouette was obtained by background subtraction and shadow elimination from video sequences. A new contour descriptor was defined, which was employed to transform the contour into a 1D distance signal. An approximating polygon was constructed by connecting the neighbor segmenting points by using line segment after equally segmenting the contour and the centroid of silhouette was obtained. The three distance strings formed with the distance from the vertexes to the center of contour and the distances from the vertexes to the two subsequence vertexes were used to describe the contour. A hierarchical clustering method was proposed to extract the key postures of human action and a human behavior sequence could be presented by a character string if a key posture was presented by a character. The edit distance was proposed to measure the similarity of the templates and the test sequences. Experiment results have shown that this method can achieve a correct recognition rate of above 85.7 %.

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赵海勇,刘志镜,张 浩.基于模板匹配的人体日常行为识别[J].湖南大学学报:自然科学版,2011,38(2):88~92

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