This paper is concerned with the use of belief theory to resolve the data association problem in the context of tracking and identifying people using audio and video data. In order to associate measurements with targets, the proposed method exploits different features such as color, position and acoustic parameters. This has the advantage of providing a robust solution to data association in challenging tracking scenarios.