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ICPR
2004
IEEE

Complex Human Activity Recognition for Monitoring Wide Outdoor Environments

9 years 6 months ago
Complex Human Activity Recognition for Monitoring Wide Outdoor Environments
The problem of automatic recognition of human activities is among the most important and challenging open areas of research in Computer Vision. This paper presents a new approach to automatically recognize complex human activities embedded in video sequences acquired with a large scale view in order to monitoring wide area (car parking, archeological site. etc) with a single static camera. The recognition process is performed in two steps: at first the human body posture is estimated frame by frame and then the temporal sequences of the detected postures are statistically modeled. Body postures are estimated starting from the binary shapes associated to humans, selecting as features the horizontal and vertical histograms and supplying them as input to an unsupervised clustering algorithm. The Manhattan distance is used for both clusters building and run-time classification. Statistical modeling of the detected postures is performed by Discrete Hidden Markov Models. The system has been...
Arcangelo Distante, I. Gnoni, Marco Leo, Paolo Spa
Added 09 Nov 2009
Updated 09 Nov 2009
Type Conference
Year 2004
Where ICPR
Authors Arcangelo Distante, I. Gnoni, Marco Leo, Paolo Spagnolo, Tiziana D'Orazio
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