3D object recognition based on curvature information of planar views

In this paper, a 3D object recognition algorithm is proposed. Objects are recognized by studying planar images corresponding to a sequence of views. Planar shape contours are represented by their adaptively calculated curvature functions, which are decomposed in the Fourier domain as a linear combin...

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Bibliographic Details
Published in:	Pattern recognition Vol. 36; no. 11; pp. 2571 - 2584
Main Authors:	de Trazegnies, C., Urdiales, C., Bandera, A., Sandoval, F.
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 01.11.2003
Subjects:	3D object recognition Curvature functions Hidden Markov models Principal component analysis 3D object recognition Curvature functions Hidden Markov models Principal component analysis
ISSN:	0031-3203, 1873-5142
Online Access:	Get full text
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Summary:	In this paper, a 3D object recognition algorithm is proposed. Objects are recognized by studying planar images corresponding to a sequence of views. Planar shape contours are represented by their adaptively calculated curvature functions, which are decomposed in the Fourier domain as a linear combination of a set of representative shapes. Finally, sequences of views are identified by means of Hidden Markov Models. The proposed system has been tested for artificial and real objects. Distorted and noisy versions of the objects were correctly clustered together.
ISSN:	0031-3203 1873-5142
DOI:	10.1016/S0031-3203(03)00166-3