Multiple Target Tracking in World Coordinate with Single, Minimally Calibrated Camera

Tracking multiple objects is important in many application domains. We propose a novel algorithm for multi-object tracking that is capable of working under very challenging conditions such as minimal hardware equipment, uncalibrated monocular camera, occlusions and severe background clutter. To address this problem we propose a new method that jointly estimates object tracks, estimates corresponding 2D/3D temporal trajectories in the camera reference system as well as estimates the model parameters (pose, focal length, etc) within a coherent probabilistic formulation. Since our goal is to estimate stable and robust tracks that can be univocally associated to the object IDs, we propose to include in our formulation an interaction (attraction and repulsion) model that is able to model multiple 2D/3D trajectories in space-time and handle situations where objects occlude each other. We use a MCMC particle filtering algorithm for parameter inference and propose a solution that enables accur...

• Type: Conference
• Year: 2010
• Where: ECCV
• Authors: Wongun Choi, Silvio Savarese
• Keywords: Camera, Coherent Probabilistic Formulation, Computer Vision, ECCV 2010, Severe Background Clutter