Abstract
This paper proposes a method for multiple people tracking in Intelligent Space (iSpace). It is difficult to obtain one complete trajectory from human tracking with computer vision. In many cases, a trajectory splits into some fragments because of errors. To solve this problem, we integrated human tracking and face recognition. First, a simple human tracking algorithm for DINDs is proposed. Then, a face recognition is applied to provide probability of identity for each fragments produced by tracking result. This probability allows us to reconstruct one true trajectory from fragments.
