An Adaptive Global Motion Estimation Method Based on Improved SUSAN Algorithm and SIFT Algorithm

摘要：

　　In order to improve the real-time of global motion estimation,we proposed a adaptive global motion estimation method based on improved SUSAN algorithm and SIFT algorithm.According to the five matching results before the current matching,the method uses Kalman filter algorithm to predict overlap regions of the current matching two images,and then extracts feature points in the overlapping regions instead of the whole regions of the images.In the part of extracting feature points of the method,improving the SUSAN algorithm according to the geometric characteristics of the SUSAN templates,which improves the speed of extracting feature points.Writing code to implement the method in VS2008,and experimental verification: This method accelerates the executing speed of the algorithm ensuring the accuracy at the same time.

关键词： Paper Instruction Chinese Control and Decision Conference

作者: Cao Luguang Zhang Huiqing

作者单位: Beijing University of Technology, Beijing 100124

会议类型: 国际会议

会议名称: the 25th Chinese Control and Decision Conference(第25届中国控制与决策会议)

会议地点: 贵阳

会议语种:英文

页码: 2815-2819

在线出版日期: 2013-05-01（万方平台首次上网日期，不代表论文的发表时间）