A combined color-correlation visual model for object tracking using particle filters

In this paper we consider the problem of tracking semi-rigid objects in video sequences using particle filters, with a particular focus on hand tracking applications. Although many different feature descriptors have been developed, none of them alone is good enough to deal with this complex tracking scenarios. Approaches which use a statistical representation of the target tend to fail in presence of visually similar objects, while holistic representations are usually very sensible to motion blur, object deformations and rotations. We present here a visual model which combines color histograms and the MOSSE Correlation Filter. The fusion of two complementary features creates a robust descriptor of the target which is capable of tracking fast moving objects in complex tracking applications with real-time performances, using a low number of particles.