Tracking and Identifying Multiple People in Multiple Camera Images

Abstract

To track and recognize the movements of multiple people using multiple cameras, each person needs to be segmented and identified in the image of each camera We describe a method that tracks multiple people and identifies their body parts in multiple camera images Estimating the positions of people and identifying the multiple cameras are mainly based on the silhouette method combining the background and frame subtraction Our method was improved by using the existence probability map on noise problems The existence probability map consists of the position probability and height cumulus maps. A gesture event is detected by comparing the human and motion blocks that are extracted from the voting space using the silhouette method We demonstrate experimental results and the validity of our method