Multi hypotheses based object tracking in HCI environments

Gesture recogntion plays an important role in Human Computer Interaction (HCI). However, in most HCI systems the user is limited to use only one hand or two hands under optimal conditions. Challenges are for instance non-homogeneous backgrounds, hand-hand or hand-face overlapping or brightness modifications which will be met in real HCI scenarios. In this work, we propose a novel method that solves the ambiguities due to the hand overlap robustly based on multi-hypotheses object association. The results of tracking build the basis for further feature extraction and gesture recognition.