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Learning and recognizing behavioral patterns using position and posture of human body and its application to detection of irregular states
Author(s) -
Aoki Shigeki,
Iwai Yoshio,
Onishi Masaki,
Kojima Atsuhiro,
Fukunaga Kunio
Publication year - 2005
Publication title -
systems and computers in japan
Language(s) - English
Resource type - Journals
eISSN - 1520-684X
pISSN - 0882-1666
DOI - 10.1002/scj.20293
Subject(s) - body position , position (finance) , artificial intelligence , computer vision , computer science , body posture , human body , pattern recognition (psychology) , communication , psychology , neuroscience , physical medicine and rehabilitation , medicine , finance , economics
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 ( www.interscience.wiley.com ). DOI 10.1002/scj.20293

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