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In this paper, we present a robust approach to real-time tracking of multiple objects in mediated environments using a set of calibrated color and IR cameras. Challenges addressed in this paper include robust object tracking in the presence of color projections on the ground plane and partial/complete occlusions. To improve tracking in such complex environment, false candidates introduced by ground plane projection or mismatching of objects between views are removed by using the epipolar constraint and the planar homography. A mixture of Gaussian is learned using the expectation-maximization algorithm for each target to further refine the 3D location estimates. Experimental results demonstrate that the proposed approach is capable of robust and accurate 3D object tracking in a complex environment with a great amount of visual projections and partial/complete occlusions.