MOTION OBJECT DETECTION METHOD BASED ON PIECEMEAL PRINCIPAL COMPONENT ANALYSIS OF DYNAMIC BACKGROUND UPDATING

摘要：

On the traditional dynamic background updating method, homomorphic filter is used to reduce influence of illumination, and temporal difference is replaced by background subtraction in order to reduce area of motion object and the influence of illumination in the area of nearby motion object. Moreover, on this improving dynamic background updating method, this paper proposes a kind of motion object detection algorithm based on piecemeal principal component analysis. Differentiating from the traditional method whose principal component analysis is used to deal with the whole image, this method carries on piecemeal processing to the whole image, and then, principal component analysis is used to deal with each block of the image in order to give prominence to the principal characteristic. And the block of this principal characteristic contains motion object. So, we can detect the motion object easily. Experimental results prove that these methods offered above resolve the problem of illumination, and the accuracy is high. Also, the operation of this algorithm is not difficult.

关键词： Background Updating Principal Component Analysis Object Detection

作者: XIAO-JUN CAO BAO-CHANG PAN SHENG-LIN ZHENG CHAO-YANG ZHANG

作者单位: Institute of Digital Image Technology, Faculty of Information Engineering, Guangdong University of Technology, Guangzhou 510006, China

会议类型: 国际会议

会议名称: 2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)

会议地点: 昆明

会议语种:英文

页码: 2932-2937

在线出版日期: 2008-07-12（万方平台首次上网日期，不代表论文的发表时间）