Two Efficient Algorithms for Outlier Removal in Multi-view Geometry Using L∞ Norm
L∞ norm has been recently introduced to multi-view geometry computation to achieve globally optimal computation. It however suffers from a serious sensitivity to outliers. A few remedies have been proposed but with high computational complexity. This paper presents two efficient algorithms to overcome these problems. Our first algorithm is based on a cheap and effective local descent method (as opposed to the conventional but expensive SOCP(Second Order Cone Programming)). The second algorithm further improves the first one by using a Depth-first search heuristics. Both algorithms retain the nice property of global op-timality of the L∞ scheme, while at cost only a small fraction of the original computation. Experiments on both synthetic data and real images have validated the proposed algorithms.
Yuchao Dai Mingyi He Hongdong Li
School of Electronics and Information, Northwestern Polytechnical University Shaanxi Key Laboratory School of Electronics and Information, Northwestern Polytechnical University Shaanxi Key Laboratory Canberra Research Lab, NICTA Research School of Information Sciences and Engineering, Australian Nat
国际会议
The Fifth International Conference on Image and Graphics(第五届国际图像图形学学术会议 ICIG 2009)
西安
英文
325-330
2009-09-20（万方平台首次上网日期，不代表论文的发表时间）