DocumentCode :
3437214
Title :
A New Approach to Geometrical Feature Assessment for ICP-Based Pose Measurement: Continuum Shape Constraint Analysis
Author :
McTavish, D.J. ; Okouneva, G.
Author_Institution :
Ryerson Univ., Toronto
fYear :
2007
fDate :
5-7 Sept. 2007
Firstpage :
23
Lastpage :
32
Abstract :
This paper presents a generalization of closest- point constraint analysis called continuum shape constraint analysis (CSCA) that can be used to assess the suitability of whole objects or object features for range data scanning and subsequent pose estimation. "Directional CSCA" (D-CSCA) is proposed to specifically address pose estimation accuracy via the ICP (iterated closest-point) family of algorithms. Constraint analysis based on noise amplification index (NAI) is used. In the D-CSCA formulation, the continuum nature of the underlying shape registration renders the resulting gradient matrix and NAI thereof as pure properties of the feature, dependent on viewpoint but independent of the viewing instrument.
Keywords :
feature extraction; image registration; closest- point constraint analysis; continuum shape constraint analysis; geometrical feature assessment; noise amplification index; range data scanning; shape registration; subsequent pose estimation; Clouds; Computer errors; Cost function; Extraterrestrial measurements; Image analysis; Iterative closest point algorithm; Laser radar; Shape measurement; Space vehicles; Symmetric matrices;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Vision and Image Processing Conference, 2007. IMVIP 2007. International
Conference_Location :
Kildare
Print_ISBN :
978-0-7695-2887-8
Type :
conf
DOI :
10.1109/IMVIP.2007.38
Filename :
4318134
Link To Document :
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