Séminaire : Minimal solutions for Homography estimation and 3D lines reconstruction

Cédric DEMONCEAUX, professeur à l'Université de Bourgogne/Le2i fera une présentation de ses travaux de recherche, lundi 10 juillet 2017 à 14h00 en salle A301 du pôle API à Illkirch sur le thème de la Vision par Ordinateur.

Titre : Minimal solutions for Homography estimation and 3D lines reconstruction

Résumé : In Computer Vision, many estimation problems typically rely on a RANSAC procedure in order to find a solution in the presence of noise and outliers. The convergence of this approach strongly depends on the number of points we need to model the problem. Thus, in order to reduce the number of iterations and consequently the running time, we have to find the minimal set of points needed to model the problem. In this talk, we will see how we can reduce this number of points using prior knowledge. First, we will talk about Homography estimation where, in the general case, we need 4 points for calculating this transformation. We will try to reduce this number of points from 4 to 2 thanks to prior information. Second, in the same way, we will focus on 3D line reconstruction in non-central camera systems. Theoretically, 4 points in a single image are sufficient in order to reconstruct a 3D line. We will see that this number of points can be reduced knowing some information about the 3D position of the camera.

Bio : Cédric Demonceaux received the MSc degree in Mathematics in 2001 and the PhD degree in Image Processing in 2004, both from the Université de Picardie Jules Verne (UPJV), France. In 2005, he became an associate professor at MIS-UPJV. From 2010 to 2014, he obtained a CNRS-Higher Education chair at Le2i UMR CNRS, University of Burgundy. Since 2014, he is full Professor at the University of Burgundy. His research interests are in Image Processing and Computer Vision for Robotics applications.