Real-time shape retrieval for robotics using skip Tri-grams

Authors:
Yi Li;Konstantinos Bitsakos;Cornelia Fermuller;Yiannis Aloimonos
Affiliations:
University of Maryland Institute for Advanced Computer Studies, University of Maryland, College Park, MD;University of Maryland Institute for Advanced Computer Studies, University of Maryland, College Park, MD;University of Maryland Institute for Advanced Computer Studies, University of Maryland, College Park, MD;University of Maryland Institute for Advanced Computer Studies, University of Maryland, College Park, MD
Venue:
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Year:
2009

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Abstract

The real time requirement is an additional constraint on many intelligent applications in robotics, such as shape recognition and retrieval using a mobile robot platform. In this paper, we present a scalable approach for efficiently retrieving closed contour shapes. The contour of an object is represented by piecewise linear segments. A skip Tri-Gram is obtained by selecting three segments in the clockwise order while allowing a constant number of segments to be "skipped" in between. The main idea is to use skip Tri-Grams of the segments to implicitly encode the distant dependency of the shape. All skip Tri-Grams are used for efficiently retrieving closed contour shapes without pairwise matching feature points from two shapes. The retrieval is at least an order of magnitude faster than other state-of-the-art algorithms. We score 80% in the Bullseye retrieval test on the whole MPEG 7 shape dataset [11]. We further test the algorithm using a mobile robot platform in an indoor environment. 8 objects are used for testing from different viewing directions, and we achieve 82% accuracy.