NDLI: Robust Estimation of Nonrigid Transformation for Point Set Registration

Content Provider	IEEE Xplore Digital Library
Author	Jiayi Ma Ji Zhao Jinwen Tian Zhuowen Tu Yuille, A.L.
Copyright Year	2013
Description	Author affiliation: Lab. of Neuro Imaging, UCLA, Los Angeles, CA, USA (Zhuowen Tu) \|\| Robot. Inst., Carnegie Mellon Univ., Pittsburgh, PA, USA (Ji Zhao) \|\| Huazhong Univ. of Sci. & Technol., Wuhan, China (Jiayi Ma; Jinwen Tian) \|\| Dept. of Stat., UCLA, Los Angeles, CA, USA (Yuille, A.L.)
Abstract	We present a new point matching algorithm for robust nonrigid registration. The method iteratively recovers the point correspondence and estimates the transformation between two point sets. In the first step of the iteration, feature descriptors such as shape context are used to establish rough correspondence. In the second step, we estimate the transformation using a robust estimator called L_2E. This is the main novelty of our approach and it enables us to deal with the noise and outliers which arise in the correspondence step. The transformation is specified in a functional space, more specifically a reproducing kernel Hilbert space. We apply our method to nonrigid sparse image feature correspondence on 2D images and 3D surfaces. Our results quantitatively show that our approach outperforms state-of-the-art methods, particularly when there are a large number of outliers. Moreover, our method of robustly estimating transformations from correspondences is general and has many other applications.
Starting Page	2147
Ending Page	2154
File Size	1531387
Page Count	8
File Format	PDF
ISBN	9780769549897
ISSN	10636919
DOI	10.1109/CVPR.2013.279
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-06-23
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Robustness Shape Maximum likelihood estimation Noise Kernel Context Mathematical model regularization L2E registration outlier nonrigid
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Software

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