Q-Gram statistics descriptor in 3d shape classification

Authors:
Evgeny Ivanko;Denis Perevalov
Affiliations:
Institute of Mathematics and Mechanics Ural Branch Russian Academy of Sciences, Ekaterinburg, Russia;Institute of Mathematics and Mechanics Ural Branch Russian Academy of Sciences, Ekaterinburg, Russia
Venue:
ICAPR'05 Proceedings of the Third international conference on Pattern Recognition and Image Analysis - Volume Part II
Year:
2005

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Abstract

In this article we propose simple descriptor for the purposes of 3D objects recognition and classification. Princeton Shape Benchmark 2004 is used for testing the proposed descriptor. Small size (512b) of the proposed descriptor and short generation and comparison times combine with relatively high recognition abilities. Surprisingly, we found that despite its simplicity and the small size the proposed descriptor took the first place in “coarser” classification test, where all 3D models were divided into 6 large classes: buildings, household, plants, animals, furniture, vehicles and a miscellaneous class not included in averaged retrieval results.