Sift-based object matching and tracking of coal mine

摘要：

Proposed a new algorithm based on Scale Invariant Feature Transform(SIFT) algorithm to suit for object matching in special environment of coal mine. New algorithm combines RANSAC with L-M nonlinear optimization algorithm after cross-matching cursorily to estimate optimization parameters, local regions of different images and angle between eigenvectors are used to reduce search scope and cost time. Experimental results show that the new algorithm has good robustness on low illumination, blur, scale change, shelter by other object and high noise condition. It can increase matching accuracy, reduce the computation for real-time processing of video surveillance and object tracking system of coal mine area.

关键词： SIFT video surveillance coal mine RANSAC L-M nonlinear optimization algorithm object matching

作者: LI Dan QIAN Jian-sheng

作者单位: Department of Information and Electric Engineering, Department of XuHai, China University of Mining Department of Information and Electric Engineering, China University of Mining and Technology, Xuzho

会议类型: 国际会议

会议名称: 2010 The IET 3rd International Conference on Wireless,Mobile & Multimedia Networks(第三届IET无线移动及多媒体网络国际会议 ICWMMN 2010)

会议地点: 北京

会议语种:英文

页码: 327-330

在线出版日期: 2010-09-26（万方平台首次上网日期，不代表论文的发表时间）