An image retrieval based solution for correspondence problem in binocular vision

Aim of this paper is to propose a solution to the correspondence problem in multi-camera systems. In these systems, two or more cameras are used to record the same scene from different view points. In this way it is possible to face the problem of occlusions in crowding scenes. In this work an object level motion detection algorithm is used and it is applied to the videos sampled by two cameras. The proposed approach does not require a calibration stage and it does not introduce any constraints about the camera positions. Once that the moving objects are detected, they are characterized using image retrieval techniques. The system was tested using two cameras. Object detection and tracking are primary tasks in automatic video streaming analysis. The obtained results in terms of correct classifications rate seem to be encouraging because they highlight the ability of the system to work also in presence of crowding scenes.