Detection of Moving Targets with a Moving Camera

摘要：

In this paper we propose a new method of detecting moving objects from a moving camera based on SIFT(The Scale Invariant Feature Transform) features matching and dynamic background modeling. Firstly, feature points are extracted by SIFT algorithm to compute the affine transformation parameters of camera motion, and guided by RANSAC to remove the outliers. We adopt background subtraction approach to detect moving objects, with shadow and ghost removing. The robustness of SIFT Features matching and the validity of picking out outliers by a RANSAC algorithm make the parameters of affine transform model to be computed accurately, and by the background subtraction approach with dynamically-updated background model, foreground objects can be detected perfectly. Experimental results demonstrate that our algorithm can detect moving objects accurately, and keep the integrity of foreground objects, comparing with optical flow method.

作者: Dongxiang Zhou Liangfen Wang Xuanping Cai Yunhui Liu

作者单位: school of Electronic Science and Engineering,National University of Defense Technology,Changsha,4100 Dept.of Automation and Computer Aided Eng.,The Chinese University of Hong Kong

会议类型: 国际会议

会议名称: 2009 IEEE International Conference on Robotics and Biomimetics(2009 IEEE 机器人与仿生技术国际会议 ROBIO 2009)

会议地点: 桂林

会议语种:英文

页码: 677-681

在线出版日期: 2009-12-19（万方平台首次上网日期，不代表论文的发表时间）