Photo-realistic recoloring of 3D point clouds
A direct camera pose computation has been developped and implemented in order to accuratly register photos over 3D point clouds obtained from laser scanners.
Mobile robot localization in urban environment
Robot or vehicle localization, using embedded devices only, is still a challenging issue. Tackling the problem using vision is full of potential since images bring a lot of information about the environment. Camera 3D pose estimation, to be consistent and precise, can benefit from two things: a 3D model of the environment, as it is well known, and the photometric appearance of the environment. The latter recently received more attention from the research community. However, it is mainly tackled for conventional cameras and using 3D models obtained from their images and for this purpose. In parallel, recent tools like 3D laser scanners have been more and more improved and are now able to rapidly generate an accurate and colored dense point clouds of a scene. We have proposed to tackle wide field of view camera 3D pose estimation using intensities of the whole image and surrounding datasets previously acquired by a 3D laser scanner. The direct use of image intensities withdraws features detection and matching issues and ensures more consistency than using geometric features.