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Shapeme histogram projection and matching for partial object recognition

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4 Author(s)
Ying Shan ; Vision Technol. Lab., Sarnoff Corp., Princeton, NJ, USA ; H. S. Sawhney ; B. Matei ; R. Kumar

Histograms of shape signature or prototypical shapes, called shapemes, have been used effectively in previous work for 2D/3D shape matching and recognition. We extend the idea of shapeme histogram to recognize partially observed query objects from a database of complete model objects. We propose representing each model object as a collection of shapeme histograms and match the query histogram to this representation in two steps: 1) compute a constrained projection of the query histogram onto the subspace spanned by all the shapeme histograms of the model and 2) 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.

Published in:

IEEE Transactions on Pattern Analysis and Machine Intelligence  (Volume:28 ,  Issue: 4 )