Human motion tracking in outdoor environment

In this paper we describe a people tracking system addressing the visual surveillance of outdoor environments. This context involves the detection of objects moving in a sequence of images acquired by a TV camera and the recognition and tracking of human figures to allow the analysis of their gestures. The proposed tracking approach does not consider the human body parts as features to be tracked, nor uses a priori body models. Moreover, also classical prediction models are useless in the specific context (visual surveillance of archaeological sites) because the behaviors identified as illegal imply a sequence of unpredictable gestures performed in a small area. The proposed method is based on the estimation of similarity between human figures segmented in the temporal sequence. The similarity score is estimated as a function of the number of corresponding feature points. The system has been verified on real image sequences acquired by a static TV camera while the gestures normally performed by intruders were simulated in a real archaeological site.