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
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