不同监控视频条件下行人动作特征三维识别方法

Three Dimensional Recognition Method of Pedestrian Movement Characteristics under Different Surveillance Video Conditions

监控视频是公共安全的重要组成部分,目前行人动作特征三维识别过程中,对于行人的三维人体模型构建能力较差,导致不同监控视频条件下三维识别异常情况较多。针对此问题,设计不同监控视频条件下行人动作特征三维识别方法。采用OpenGL处理软件构建人体骨架模型,根据立体特征匹配算法以及人体模型构建结果,实现行人动作特征匹配。构建特征识别决策树,完成行人动作特征三维识别。至此,不同监控视频条件下行人动作特征三维识别方法设计完成。在多种分辨率情况下进行对比实验,实验结果表明,该方法三维识别结果识别失误次数最少,识别能力更佳。

Surveillance video is an important part of public security.At present,in the process of three-dimensional recognition of pedestrian movement features,the ability of building three-dimensional human body model for pedestrian is poor,which leads to many abnormalities in three-dimensional recognition under different surveillance video conditions.In order to solve this problem,a three-dimensional recognition method of pedestrian movement features under different surveillance video conditions is designed.Using OpenGL processing software to build the human skeleton model,according to the stereo feature matching algorithm and the results of human model construction,the pedestrian movement feature matching is realized.The feature recognition decision tree is constructed to complete the three-dimensional recognition of pedestrian movement features.At this point,the design of three-dimensional recognition method for pedestrian movement characteristics under different surveillance video conditions is completed.The experimental results show that the method has the least number of errors and better recognition ability.