DocumentCode
2483013
Title
Probabilistic mixtures of differential profiles for shape recognition
Author
Ding, Lei ; Belkin, Mikhail
Author_Institution
Dept. of Comput. Sci. & Eng., Ohio State Univ., Columbus, OH
fYear
2008
fDate
8-11 Dec. 2008
Firstpage
1
Lastpage
4
Abstract
We present a new shape descriptor, the differential profile, for shape representation and recognition, which is derived from differential and geometric quantities evaluated at points on a shape. We model differential profiles from a class of shapes as a finite mixture of Gaussians, and use an expectation-maximization (EM) procedure for class-wise model learning. Experiments on handwritten digit and 3D object datasets give promising results.
Keywords
Gaussian processes; expectation-maximisation algorithm; shape recognition; 3D object datasets; Gaussians finite mixture; differential profile; expectation-maximization procedure; handwritten digit; shape descriptor; shape recognition; shape representation; Application software; Biomedical imaging; Character recognition; Computer science; Computer vision; Gaussian processes; Handwriting recognition; Histograms; Shape measurement; Smoothing methods;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition, 2008. ICPR 2008. 19th International Conference on
Conference_Location
Tampa, FL
ISSN
1051-4651
Print_ISBN
978-1-4244-2174-9
Electronic_ISBN
1051-4651
Type
conf
DOI
10.1109/ICPR.2008.4761490
Filename
4761490
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