An appearance-based body model for multiple people tracking

摘要

We describe an appearance-based human body model for tracking multiple people when they are interaction with each others causing significant occlusion amongst them, or when they re-enter the scene. The proposed model allows real time surveillance systems understand "who is who" after multiple people interactions, partial or total occlusions, or when a person "reappeal" in the scene. It combines the grayscale textural appearance and expected shape information together in a 2D dynamic template. Experimental results demonstrates the robustness and real time performance of the proposed model.