Symbolic signatures for deformable shapes

Recognizing classes of objects from their shape is an unsolved problem in machine vision that entails the ability of a computer system to represent and generalize complex geometrical information on the basis of a finite amount of prior data. A practical approach to this problem is particularly diffi...

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Bibliographic Details
Published in:	IEEE transactions on pattern analysis and machine intelligence Vol. 28; no. 1; pp. 75 - 90
Main Authors:	Ruiz-Correa, S., Shapiro, L.G., Meila, M., Berson, G., Cunningham, M.L., Sze, R.W.
Format:	Journal Article
Language:	English
Published:	Los Alamitos, CA IEEE 01.01.2006 IEEE Computer Society The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Algorithms Application software Applied sciences Artificial Intelligence Biometry - methods Computer science; control theory; systems Computer vision craniofacial malformations craniosynostosis deformable shapes Deformation Exact sciences and technology Face - anatomy & histology Formability Humans Image analysis Image Interpretation, Computer-Assisted - methods Imaging, Three-Dimensional - methods Index Terms- Three-dimensional object recognition and classification Layout Machine vision Medical diagnosis Mercer kernel numeric and symbolic signatures Object recognition Pattern Recognition, Automated - methods Pattern recognition. Digital image processing. Computational geometry Photogrammetry - methods Photography - methods range data Recognition Representations Reproducibility of Results Robot vision systems Robustness scene analysis Sensing devices Sensitivity and Specificity Shape Shape recognition Subtraction Technique Three dimensional Computer vision Mercer kernel Image processing Craniosynostosis Three dimensional shape Digital signal numeric and symbolic signatures craniofacial malformations deformable shapes Scene analysis Tridimensional image Pattern analysis range data Medical application Three-dimensional object recognition and classification
ISSN:	0162-8828, 1939-3539
Online Access:	Get full text
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