【摘要】 针对现有的视频监控技术仅依赖人眼的检测,缺乏智能性,进行了基于步态识别的智能监控系统研究,应用背景减除法分割出人体轮廓。通过人体宽高比的相关信号确定运动周期,再对二值周期序列进行步态能量图像(GEI)合成。运用主成分分析或行列相结合的二维主成分分析((2D)2PCA)提取特征主向量,采用最近邻分类器分类。实验结果表明,该方法可以有效降低前期处理对分类识别的影响,而且在我们自己建立的摄像头摆放有一定俯角的步态数据库中3个视角下取得很好的识别效果。更多还原

【Abstract】 In view of the existing video frequency monitoring technology only relies on the human eye for the examination and lacks intelligence,this article carried out research into the supervisory system based on the gait recognition intelligence.A novel gait representation was proposed.Body silhouette extraction was achieved by background subtraction.A gait cycle was obtained by the correlated signal of the ratio of width and height of human body.Gait energy image was applied on the binary image sequence to construct the feature vector.Then PCA or(2D)2PCA was used to reduce into a low dimension space.The nearest-neighbor classifier was adopted to distinguish.This gait recognition method can decrease the influence of the early preprocess effectively;moreover,it makes very good recognition progress under the three visual angles of our gait database in which the camera is put with certain angle of depression.更多还原