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In this paper, we present a new approach for the stable tracking of variable interacting targets under severe occlusion in 3D space. We formulate the state of multiple targets as a union state space of each target, and recursively estimate the multi-body configuration and the position of each target in 3D space by using the framework of Trans-dimensional Markov Chain Monte Carlo(MCMC). The 3D environmental model, which replicates the real-world 3D structure, is used for handling occlusions created by fixed objects in the environment, and reliably estimating the number of targets in the monitoring area. Experiments show that our system can stably track multiple humans that are interacting with each other and entering and leaving the monitored area.