Research on Wide Baseline Stereo Matching Based on PCA-SIFT

摘要：

SIFT feature matching algorithm, which has good robustness to image rotation and zoom scale, is a certain degree of stability on the angle changes and affine transformation. It also has the more stable match capacity on images which are taken from any point of view. It has been widely used in the field of wide baseline stereo matching. But the biggest problem is that extracts too many feature points, template too big and takes up more the memory. The higher dimension is also to make the matching speed down. To solve this problem, it constitutes PCA-SIFT which combined with principle component analysis (PCA) and SIFT. Compared with SIFT algorithm, the descriptors provide significant benefits in storage space and matching speed. It can reduce feature points, lower dimension of feature vector and improve matching speed. Experiments demonstrate that PCA-SIFT descriptors are more distinctive, more robust to image deformations, and more compact than standard SIFT.

关键词： PCA-SIFT wide baseline stereo matching

作者: Yong Zhang Kai-Bin Wei

作者单位: Lanzhou University of TechnologySchool of computer and communicationGansu, Lanzhou, P.R.China Lanzhou University of Technology School of computer and communication Gansu, Lanzhou, P.R.China

会议类型: 国际会议

会议名称: 2010 3rd International Conference on Advanced Computer Theory and Engineering(2010年第三届先进计算机理论与工程国际会议 ICACTE 2010)

会议地点: 成都

会议语种:英文

页码: 1-4

在线出版日期: 2010-08-20（万方平台首次上网日期，不代表论文的发表时间）