Cooperation of Passive Vision Systems in Detection and Tracking of Pedestrians

This work presents a cooperative approach for detecting and tracking pedestrians in an urban environment. Its originality lies in the cooperation of two vision systems. A monocular vision system retrieves feature elements and these elements are visualized. However, false detection can occur due to objects whose outline is similar to that of a pedestrian. This problem is solved by the introduction of an auto-adaptive stereovision algorithm that recovers all the vertical 3D segments of the scene. This cooperation supplies a fast and robust method for detecting pedestrian presence. Then, it allows for pedestrian tracking through multiple images.