Posture classification is a key process for analyzing thepeople’s behaviour. Computer vision techniques can behelpful in automating this process, but clutteredenvironments and consequent occlusions make this taskoften difficult. Different views provided by multiplecameras can be exploited to solve occlusions by warpingknown object appearance into the occluded view. To thisaim, this paper describes an approach to postureclassification based on projection histograms, reinforcedby HMM for assuring temporal coherence of the posture.The single camera posture classification is then exploitedin the multi-camera system to solve the cases in which theocclusions make the classification impossible.Experimental results of the classification from both thesingle camera and the multi-camera system are provided.
Posture Classification in a Multi-camera Indoor Environment / Cucchiara, R.; Prati, A.; Vezzani, R.. - STAMPA. - 1:(2005), pp. 725-728. (Intervento presentato al convegno IEEE International Conference on Image Processing 2005, ICIP 2005 tenutosi a Genova, ita nel 11-14 Sept.) [10.1109/ICIP.2005.1529853].
Posture Classification in a Multi-camera Indoor Environment
Cucchiara R.;Vezzani R.
2005
Abstract
Posture classification is a key process for analyzing thepeople’s behaviour. Computer vision techniques can behelpful in automating this process, but clutteredenvironments and consequent occlusions make this taskoften difficult. Different views provided by multiplecameras can be exploited to solve occlusions by warpingknown object appearance into the occluded view. To thisaim, this paper describes an approach to postureclassification based on projection histograms, reinforcedby HMM for assuring temporal coherence of the posture.The single camera posture classification is then exploitedin the multi-camera system to solve the cases in which theocclusions make the classification impossible.Experimental results of the classification from both thesingle camera and the multi-camera system are provided.Pubblicazioni consigliate
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