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In this paper an activity recognition algorithm based on multi-feature fuzzy cluster is designed to find out more details of the activities so as to achieve an accurate classification among them. Firstly, it is proved that distribution of feature vectors vary from activity to activity. And then, a multi-feature extraction algorithm is designed to extract the feature vectors of each activity which makes up a standard activity class. Finally, an activity recognition algorithm based on similarity measurement is brought up and the misjudgment rate turns out to be acceptable, which proves that this algorithm is accurate and highly feasible.