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In this paper, we present results of our algorithm for automatically estimating a subject's skeletal structure from optical motion capture data. Our algorithm consists of a series of steps that cluster markers into groups representing body segments, determine their topological connectivity, and locate the positions of the connecting joints. Our results show that the system works reliably even when only one or two markers are attached to each segment. We tested an implementation of this algorithm with both passive and active motion capture data and found it to work well. Its computed skeletal estimates closely match measured values, and the algorithm behaves robustly in the presence of noise, marker occlusion, and other errors typical of motion capture data.