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Euclidean 3D Reconstruction of Unknown Objects from Multiple Images

Soulaiman El Hazzat, Abderrahim Saaidi, and Khalid Satori
LIIAN, Dep. of Mathematics and Informatics, Faculty of Sciences Dhar-Mahraz, Fes, Morocco
Abstract—In this paper, we are interested in the problem of Euclidean 3D reconstruction of unknown objects by passive stereo vision method. Our method is based on the combination between Harris and Sift interest point detectors, to take advantage of the power of these two detectors, which will be useful when matching step, as a key step for 3D reconstruction, In order to have a sufficient number of matches distributed on the images. These matches will be used to estimate the 3D points (the projection matrices will be estimated after calibration using 3D Calibration Pattern). Finally, a 3D mesh is constructed by 3D Delaunay triangulation, applied to the 3D points reconstructed. Experimental results prove that this method is practical and gives satisfying results without going through the propagation step.
 
Index Terms—interest points, matching, calibration, 3D reconstruction, 3D mesh, 3D delaunay triangulation

Cite: Soulaiman El Hazzat, Abderrahim Saaidi, and Khalid Satori, "Euclidean 3D Reconstruction of Unknown Objects from Multiple Images," Journal of Emerging Technologies in Web Intelligence, Vol. 6, No. 1, pp. 59-63, February 2014. doi:10.4304/jetwi.6.1.59-63
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