期刊
IMAGE AND VISION COMPUTING
卷 23, 期 3, 页码 299-309出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.imavis.2004.05.007
关键词
registration; point sets; iterative closest point; least trimmed squares; robustness
The problem of geometric alignment of two roughly pre-registered, partially overlapping, rigid, noisy 3D point sets is considered. A new natural and simple, robustified extension of the popular Iterative Closest Point (ICP) algorithm [IEEE Trans. Pattern Anal. Machine Intell. 14 (1992) 239] is presented, called Trimmed ICP (TrICP). The new algorithm is based on the consistent use of the Least Trimmed Squares approach in all phases of the operation. Convergence is proved and an efficient implementation is discussed. TrICP is fast, applicable to overlaps under 50%, robust to erroneous and incomplete measurements, and has easy-to-set parameters. ICP is a special case of TrICP when the overlap parameter is 100%. Results of a performance evaluation study on the SQUID database of 1100 shapes are presented. The tests compare TrICP and the Iterative Closest Reciprocal Point algorithm [Fifth International Conference on Computer Vision, 1995]. (C) 2004 Elsevier B.V. All rights reserved.
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