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Cyclic motion underlies several human activities including exercising,running, and walking. Accurate tracking of such motion in video data helps in developing computer-aided applications such as gait analysis, person identification, patient rehabilitation, etc. This paper presents a set of novel techniques for tracking cyclic human motion based on decomposing complex cyclic motion into simpler motion components and introducing phase coupling between the components. The intensity of coupling isdoi:10.1109/icip.2003.1247250 dblp:conf/icip/ChangAK03 fatcat:vcdjsujyojfwteo66jbjdk7xoi