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Object pose from 2-D to 3-D point and line correspondences

Thai-Quynh Phong 1, 2, 3 Radu Horaud 1, 2 Adnan Yassine 4 Pham-Dinh Tao 3 
1 MOVI - Modeling, localization, recognition and interpretation in computer vision
GRAVIR - IMAG - Laboratoire d'informatique GRAphique, VIsion et Robotique de Grenoble, Inria Grenoble - Rhône-Alpes, CNRS - Centre National de la Recherche Scientifique : FR71
Abstract : In this paper we present a method for optimally estimating the rotation and translation between a camera and a 3-D object from point and/or line correspondences. First we devise an error function and second we show how to minimize this error function. The quadratic nature of this function is made possible by representing rotation and translation with a dual number quaternion. We provide a detailed account of the computational aspects of a trust-region optimization method. This method compares favourably with Newton's method which has extensively been used to solve the problem at hand, with Faugeras-Toscani's linear method (Faugeras and Toscani 1986) for calibrating a camera, and with the Levenberg-Marquardt non-linear optimization method. Finally we present some experimental results which demonstrate the robustness of our method with respect to image noise and matching errors.
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Thai-Quynh Phong, Radu Horaud, Adnan Yassine, Pham-Dinh Tao. Object pose from 2-D to 3-D point and line correspondences. International Journal of Computer Vision, 1995, 15 (3), pp.225--243. ⟨10.1007/BF01451742⟩. ⟨inria-00590044⟩



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