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It is generally considered that human behavior includes both regularities and habits. In this paper, the regularities and habits of behavior are called the behavioral pattern, and we wish to learn and recognize them. The conventional approaches considered behavioral patterns but used only infrared sensors or information about whether electrical appliances were on or off. Thus, it was difficult to recognize in detail how a person was performing motions in the room. In order to realize a procedure for the detailed recognition of motion in ordinary environments, on the other hand, a large number of models must be prepared beforehand. To deal with this problem, this paper proposes the following technique. Motions conducted in the learning period are automatically classified and individual models are constructed. Then, motions can be recognized in detail without preparing a large number of models, and behavioral patterns can be recognized by considering the sequence of motions. In experiments, human motions and behavioral patterns in an indoor environment were learned and recognized, and the effectiveness of the method was demonstrated. © 2005 Wiley Periodicals, Inc. Syst Comp Jpn, 36(13): 45–56, 2005; Published online in Wiley InterScience (). DOI 10.1002/scj.20293