This paper describes an algorithm for multiple object tracking that takes a new occlusion reasoning approach. In order to track individual objects under occlusion conditions, we design a 2D token-based tracking system using Kalman filtering. The proposed tracking system consists of two parts: object detection and tracking, and occlusion reasoning using feature matching. The object detection and tracking part finds moving objects from their background. For object detection, we develop an adaptive background update technique. By tracking individual objects with segmentation information, we generate motion trajectories. Computer simulation of the proposed scheme demonstrates its robustness to various occlusion conditions for several test sequences.