[Show abstract][Hide abstract] ABSTRACT: In this paper, we propose a very reliable and flexible method for self-calibrating rotating and zooming cameras - generally referred to as PTZ (Pan-Tilt-Zoom) cameras. The proposed method employs a Linear Matrix Inequality (LMI) resolution approach and allows extra tunable constraints on the intrinsic parameters to be taken into account during the process of estimating these parameters. Furthermore, the considered constraints are simultaneously enforced in all views rather than in a single reference view. The results of our experiments show that the proposed approach allows for significant improvement in terms of accuracy and robustness when compared against state of the art methods.
Proceedings of the 11th Asian Conference on Computer Vision. 01/2012;
[Show abstract][Hide abstract] ABSTRACT: An effective technique for applying visual tracking algorithms to omnidirectional image sequences is presented. The method is based on a spherical image representation which allows taking into account the distortions and nonlinear resolution of omnidirectional images. Experimental results show that both deterministic and probabilistic tracking methods can effectively be adapted in order to robustly track an object with an omnidirectional camera.
[Show abstract][Hide abstract] ABSTRACT: Visual tracking in video sequences is a widely developed topic in computer vision applications. However, the emergence of panoramic vision using catadioptric sensors has created the need for new approaches in order to track an object in this type of images. Indeed the non-linear resolution and the geometric distortions due to the insertion of the mirror, make tracking in catadioptric images a very challenging task. This paper describes particle filter for tracking moving object over time using a catadioptric sensor. In this work different problems due to the specificities of the catadioptric systems such as geometry are considered. The obtained results demonstrate an important improvement of the tracking accuracy with our adapted method and a better robustness to clutter background and light changes.
IEEE International Conference on Computer Vision Workshops, ICCV 2011 Workshops, Barcelona, Spain, November 6-13, 2011; 01/2011