A new normalized method on line-based homography estimation

Authors:
Hui Zeng;Xiaoming Deng;Zhanyi Hu
Affiliations:
National Laboratory of Pattern Recognition (NLPR), Institute of Automation, Chinese Academy of Sciences, P.O. Box 2728, Beijing 100080, PR China;National Laboratory of Pattern Recognition (NLPR), Institute of Automation, Chinese Academy of Sciences, P.O. Box 2728, Beijing 100080, PR China;National Laboratory of Pattern Recognition (NLPR), Institute of Automation, Chinese Academy of Sciences, P.O. Box 2728, Beijing 100080, PR China
Venue:
Pattern Recognition Letters
Year:
2008

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Abstract

It is a conventional belief that line-based approaches perform better than point-based ones for homography estimation, as the line-fitting is generally more noise resistant than point detection. In this note, we show that blithely using line-based estimation is a risky business. More specifically, we show that when the image line(s) is (are) passing through or close to the origin, the line-based homography estimation could become wildly unstable whereas the point-based estimation performs normally. To tackle this problem, a new normalized method specially designed for line-based homography estimation is proposed and validated by extensive experiments.