Pose estimation combining synthetic discriminant function filters and neural networks

Maria-Albertina Castro; Yann Frauel; Eduardo Tepichin-Rodriguez; Bahram Javidi

doi:10.1117/12.469139

27 November 2002 Pose estimation combining synthetic-discriminant-function filters and neural networks

Maria-Albertina Castro, Yann Frauel, Eduardo Tepichin-Rodriguez, Bahram Javidi

Proceedings Volume 4789, Algorithms and Systems for Optical Information Processing VI; (2002) https://doi.org/10.1117/12.469139
Event: International Symposium on Optical Science and Technology, 2002, Seattle, WA, United States

Abstract

The two-dimensional view, obtained with a camera, of a three-dimensional (3-D) object varies with the 3-D orientation of this object, complicating the recognition task. In this work we address the problem of estimating the pose of a 3-D object knowing only a 2-D projection. The proposed technique is based on a combination of synthetic-discriminant-function filters and neural networks. We succeed in estimating two orientations: in-plane and out-of-plane rotations within a 8 degree square range.

Citation Download Citation

Maria-Albertina Castro, Yann Frauel, Eduardo Tepichin-Rodriguez, and Bahram Javidi "Pose estimation combining synthetic-discriminant-function filters and neural networks", Proc. SPIE 4789, Algorithms and Systems for Optical Information Processing VI, (27 November 2002); https://doi.org/10.1117/12.469139

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