NDLI: Posture classification in a multi-camera indoor environment

Content Provider	IEEE Xplore Digital Library
Author	Cucchiara, R. Prati, A. Vezzani, R.
Copyright Year	2005
Description	Author affiliation: Dipt. di Ingegneria dell'Informazione, Univ. of Modena & Reggio Emilia, Italy (Cucchiara, R.)
Abstract	Posture classification is a key process for analyzing the people's behaviour. Computer vision techniques can be helpful in automating this process, but cluttered environments and consequent occlusions make this task often difficult. Different views provided by multiple cameras can be exploited to solve occlusions by warping known object appearance into the occluded view. To this aim, this paper describes an approach to posture classification based on projection histograms, reinforced by HMM for assuring temporal coherence of the posture. The single camera posture classification is then exploited in the multi-camera system to solve the cases in which the occlusions make the classification impossible. Experimental results of the classification from both the single camera and the multi-camera system are provided.
File Size	208441
File Format	PDF
ISBN	0780391349
DOI	10.1109/ICIP.2005.1529853
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-09-14
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Indoor environments Cameras Computer vision Biological system modeling Humans Domestic safety Shape Histograms Hidden Markov models Medical services
Content Type	Text
Resource Type	Article

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