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2004 | OriginalPaper | Buchkapitel

Partial Object Matching with Shapeme Histograms

verfasst von : Y. Shan, H. S. Sawhney, B. Matei, R. Kumar

Erschienen in: Computer Vision - ECCV 2004

Verlag: Springer Berlin Heidelberg

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Histogram of shape signature or prototypical shapes, called shapemes, have been used effectively in previous work for 2D/3D shape matching & recognition. We extend the idea of shapeme histogram to recognize partially observed query objects from a database of complete model objects. We propose to represent each model object as a collection of shapeme histograms, and match the query histogram to this representation in two steps: (i) compute a constrained projection of the query histogram onto the subspace spanned by all the shapeme histograms of the model, and (ii) compute a match measure between the query histogram and the projection. The first step is formulated as a constrained optimization problem that is solved by a sampling algorithm. The second step is formulated under a Bayesian framework where an implicit feature selection process is conducted to improve the discrimination capability of shapeme histograms. Results of matching partially viewed range objects with a 243 model database demonstrate better performance than the original shapeme histogram matching algorithm and other approaches.

Metadaten
Titel
Partial Object Matching with Shapeme Histograms
verfasst von
Y. Shan
H. S. Sawhney
B. Matei
R. Kumar
Copyright-Jahr
2004
Verlag
Springer Berlin Heidelberg
DOI
https://doi.org/10.1007/978-3-540-24672-5_35

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