Nour Eddine Mohtaram, PhD.

Football Player Analysis System

- Applied deep learning in Face detection, recognition, identification, specifically use FCN model to train a predictor capable of calculating the number of people in a large area. - Data engineering (Docker container). - Hardware ecosystem: GPU, cluster of distributed computing.. - Code optimisation and profiling (Valgrind, Gprof) . - Object detection and tracking using an Intel depth sensing camera RealSense D435 . - Tools: C++, Python, Pytorch, OpenCV, bash, FCN, Numpy, Scipy, Pandas, Git, Docker, Unix.

This PhD work focuses on the problem of complete dense 3D reconstruction of objects without recoil. We have conceived and developped a tridimensional reconstruction system of real objects based on a camera with two planar mirrors ; baptised as a Planar Catadioptric Stereo (PCS) system. We first model the PCS system by a network of virtual cameras to perform calibration. Then, we formulate the problem of characteristic points’ correspondences detected on the reflected images by using a variant of the ASIFT method. This adaptation which we behold as AMIFT on the mirror planes. Putative point correspondences are further refined with oulier rejection using our method of Symmetric RANSAC proposed in this thesis. To reconstruct a proper dense object surface, and not just a sparse projection of points, a dense correspondence technique is consequently required. This method estimates the geometric transformation linking the image object with one of it’s inter reflections on the mirror planes by minimising a branch and bound cost function. This allows us to adapt the 3D dense reconstruction, fundamentally based on the triangulation of image correspondences. We apply this 3D reconstruction pipeline on multiple catadioptric images in order to verify the undermining hypothesis using a PCS system. Our methodology is validated using experimental results on synthetic images to illustrate the quality of the 3D reconstruction.

Teaching assistant for undegraduate courses in C programming & Operating system.

sujet : Réalisation d’une application 3D des statues sans recul dans le but de réaliser et compléter un modèle de numérisation 3D d’un édifice. outils : Matlab, c++

sujet: Conception et Réalisation d’une application de Gestion de bureau d’ordre. outils: php, framework zend, Mysql conception: UML

sujet : Interface graphique permettant la visualisation de solutions pour des problèmes d’optimisation multi-objectif en se basant sur les algorithmes multi-objectif sur les problèmes DTLZ. outils: Java conception: UML