Active object recognition based on Fourier descriptors clustering

Authors:
Elizabeth González;Antonio Adán;Vicente Feliú;Luis Sánchez
Affiliations:
E.T.S. Ingenieros Industriales, University of Castilla La Mancha, Avda. Camilo José Cela s/n, Ciudad Real 13071, Spain;E. Superior de Informática, University of Castilla La Mancha, Ronda de Calatrava 5, Ciudad Real 13071, Spain;E.T.S. Ingenieros Industriales, University of Castilla La Mancha, Avda. Camilo José Cela s/n, Ciudad Real 13071, Spain;E.U. Ingeniería Técnica Industrial, University of Castilla La Mancha, Campus Tecnológico Antigua Fábrica de Armas, Toledo 45071, Spain
Venue:
Pattern Recognition Letters
Year:
2008

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Abstract

This paper presents a new 3D object recognition/pose strategy based on Fourier descriptors clustering for silhouettes. The method consists of two parts. Firstly, an off-line process calculates and stores a clustered Fourier descriptors database corresponding to the silhouettes of the synthetic model of the object viewed from multiple viewpoints. Next, an on-line process solves the recognition/pose problem for an object that is sensed by a camera placed at the end of a robotic arm. The method solves the ambiguity problem - due to object symmetries or similar projections belonging to different objects - by taking a minimum number of additional views of the scene which are selected through a heuristic next best view (NBV) algorithm. The method works in reduced computational time conditions and provides identification and pose of the object. A validation test of this method has been carried out in our lab yielding excellent results.