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Unsupervised discovery of basic human actions from activity recording datasets
2012
2012 IEEE/SICE International Symposium on System Integration (SII)
Human Behavior Understanding (HBU) is a major challenge facing intelligent agents. Most approaches to solve this problem assume a recognition/detection context in which the agent/robot tries to match the perceived behavior to one or more predefined motion patterns (e.g. walking, running etc). A more challenging problem is discovering these motion patterns without apriori assumption about the motions in the data, their duration or their numbers. This paper proposes the utilization of a novel
doi:10.1109/sii.2012.6426960
fatcat:4qcrv6tqqnehplkqf3ubblhqsq