Mohamed Bénallal

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In this paper we propose a method for locating a point (or object) in space without any camera calibration or object model. Instead we assume that the 2D location of 4 coplanar points is known and that the unknown point lay on this plane. This is similar to computing the fundamental matrix linking pixel position in the image plane with another plane(More)
Using measurements of Sea Surface Salinity and Sea Surface Temperature in the Western we compare two approaches for estimating Sea Surface Salinity : Multiple Non-linear Regression and Multi Layer Perceptron. In the first experiment, we use 18,300 in situ data points to establish the two models, and 503 points for testing their extrapo-lation. In the second(More)
relating the coordinates of the vertex A and its projection a with the direction cosines: In this paper we model the camera-polygon system with parametric equations to locate a polygonal object in space. cosa. = J-This leads to a nonlinear optimization method under true X +YO +fa perspective for monocular vision with a single image. The algorithm finds(More)
To answer the industrial need for simple camera calibration procedure, we propose a new method that requires a simple calibration object composed simply of a box and two crosses. The box is opened in the front where a large cross, made of wires, is attached while another is drawn (or attached) at the bottom. Both crosses are perfectly aligned similarly to a(More)
We propose an iterative method of 3D localization of 2D or 3D polygonal shapes by monocular vision from a sngle image. The method assumes that the size of the polygonal object is known and that the camera is calibrated. Essentially, the 3D localization is obtained by the resolution of a non-linear system using the parametric equations of the polygonal(More)
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