Efficient search and verification for function based classification from real range images

  • Authors:
  • Guy Froimovich Ehud Rivlin;Ilan Shimshoni;Octavian Soldea

  • Affiliations:
  • Department of Computer Science, The Technion, Israel Institute of Technology, Haifa, Israel;Department of Management Information Systems, University of Haifa, Haifa, Israel;Department of Computer Science, The Technion, Israel Institute of Technology, Haifa, Israel

  • Venue:
  • Computer Vision and Image Understanding
  • Year:
  • 2007

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Abstract

In this work we propose a probabilistic model for generic object classification from raw range images. Our approach supports a validation process in which classes are verified using a functional class graph in which functional parts and their realization hypotheses are explored. The validation tree is efficiently searched. Some functional requirements are validated in a final procedure for more efficient separation of objects from non-objects. The search employs a knowledge repository mechanism that monotonically adds knowledge during the search and speeds up the classification process. Finally, we describe our implementation and present results of experiments on a database that comprises about 150 real raw range images of object instances from 10 classes.