基于正弦级数拟合的行为识别方法  

Action Recognition Based on Sine Series Fitting

作　　者：赵绚[1,2] 彭启民[1] 

机构地区：[1]中国科学院软件研究所天基综合信息系统重点实验室,北京100190 [2]中国科学院大学,北京100049

出　　处：《计算机研究与发展》2013年第2期379-386,共8页Journal of Computer Research and Development

摘　　要：提出了一种基于正弦级数拟合的行为识别方法.该方法利用二值轮廓序列来表示给定的运动图像序列,按照时针顺序计算从轮廓质心到轮廓边界点的距离,将人体轮廓转化为距离曲线,并将这一距离曲线利用正弦级数进行拟合,将距离曲线转化为正弦参数,从而极大地减小了计算量,将行为识别过程转化为曲线参数特征匹配的过程.在特征匹配过程中,通过计算待预测行为与已知类别行为的特征级数距离,对待预测行为中的每一个动作进行分类,最后通过投票决定该行为所属类别.在包含90个不同运动类别的视频数据库上进行留一交叉验证,实验结果表明,提出的方法能够有效地进行人体行为识别.This paper presents a sine series-based method for action recognition. The proposed method can be divided into three stages, feature extraction, series fitting and feature matching. In the stage of feature extraction, the method gets binary human silhouette through background difference and Gaussian background modeling at first, then uses the binary silhouette to represent the given image sequence and calculates the distance from the silhouette centroid to the boundary points according to a clockwise movement, thus changing the human silhouette into distance curve. In the stage of series fitting, the method fits the curve with the sine series and changes the distance curve into sine parameters with different amplitude, frequency and offset, which reduces the computational cost greatly and changes the process of action recognition into the matching of curve parameter features. Finally, in the stage of feature matching, the method classifies each frame in the given image sequence through calculating the minimum distance between it and the known action categories at first, and then gets the category of the given image sequence by voting. We adopt a leave-one-out scheme for experiment evaluation. The experiment results on a database of 90 short video sequences show that the promising performance is both effective and efficient.

关 键 词：行为识别 轮廓距离曲线 参数拟合 正弦级数 特征匹配 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]