Rotation-Invariant DAISY Descriptor for Keypoint Matching and Its Application in 3D Reconstruction
In this paper, we introduce an improved version of DAISY descriptor algorithm, which is used for high-quality image keypoint matching. Since DAISY descriptor algorithm has many prominent advantages but lacks the ability of handling large in-plane rotation, we thus construct our Rotation-Invariant DAISY descriptor to effectively settle this shortcoming. The matching results of our scheme can be also used into 3D reconstruction task. After camera parameters are estimated by self-calibration, we compute corresponding 3D data using structure from motion (SFM) technique. Our experimental results demonstrate that Rotation-Invariant DAISY descriptor algorithm has better performance in various image distortions, and it can be effectively applied to the framework of 3D reconstruction.
Yin Guo Hui Zeng Zhi-Chun Mu Feng Zhang
School of Information Engineering, University of Science and Technology Beijing No.30, Xueyuan Road, Haidian, Beijing, China
国际会议
2010 IEEE 10th International Conference on Signal Processing(第十届信号处理国际会议 ICSP 2010)
北京
英文
1198-1201
2010-08-24（万方平台首次上网日期，不代表论文的发表时间）