AD-HOC : Appearance Driven Human tracking with Occlusion Handling

AD-HOC copes with the problem of multiple people tracking in video surveillance in presence of large occlusions. The main novelty is the adoption of an appearance-based approach in a formal Bayesian framework: the status of each object is defined at pixel level, where each pixel is characterized by the appearance, i.e. the color (integrated along the time) and the likelihood to belong to the object. With these data at pixel-level and a probability of non-occlusion at object-level, the problem of occlusions is addressed. The method does not aim at detecting the presence of an occlusion only, but classifies the type of occlusion at a sub-region level and evolve the status of the object in a selective way. The AD-HOC tracking has been tested in many application for indoor and outdoor surveillance. Results on PETS2006 test set are reported where many people and abandoned objects are detected and tracked.