Video surveillance has a direct application in intelligent home automation or domotics (from the Latin word domus, that means “home”, and informatics). In particular, in-house video surveillance can provide good support for people with some difficulties (e.g. elderly or disabled people) living alone and with limited autonomy. A key aspect in video surveillance systems for domotics is that of analyzing behaviours of the monitored people. To accomplish this task, people must be detected and tracked, and their posture must be analyzed in order to model behaviours recognizing abrupt changes in it. Problems related to reliable software solutions are not completely solved, in particular luminance changes, shadows and frequent posture changes must be taken into account. Long-lasting occlusions are common due to the proximity of the cameras and the presence of furniture and doors that can often hide parts of a person’s body. For these reasons, a probabilistic and appearance-based tracking, particularly conceivable for people tracking and posture classification, has been developed. However, despite its effectiveness for long-lasting and large occlusions, this approach tends to fail whenever the person is monitored with multiple cameras and he appears in one of them already occluded. 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.

Making the home safer and more secure through visual surveillance / Cucchiara, Rita; Prati, Andrea; Vezzani, Roberto. - STAMPA. - 1:(2005), pp. 172-175. ((Intervento presentato al convegno 5th International Conference on Methods and Techniques in Behavioral Research tenutosi a Wageningen, The Netherlands nel 30 August - 2 September 2005.

Making the home safer and more secure through visual surveillance

CUCCHIARA, Rita;PRATI, Andrea;VEZZANI, Roberto
2005-01-01

Abstract

Video surveillance has a direct application in intelligent home automation or domotics (from the Latin word domus, that means “home”, and informatics). In particular, in-house video surveillance can provide good support for people with some difficulties (e.g. elderly or disabled people) living alone and with limited autonomy. A key aspect in video surveillance systems for domotics is that of analyzing behaviours of the monitored people. To accomplish this task, people must be detected and tracked, and their posture must be analyzed in order to model behaviours recognizing abrupt changes in it. Problems related to reliable software solutions are not completely solved, in particular luminance changes, shadows and frequent posture changes must be taken into account. Long-lasting occlusions are common due to the proximity of the cameras and the presence of furniture and doors that can often hide parts of a person’s body. For these reasons, a probabilistic and appearance-based tracking, particularly conceivable for people tracking and posture classification, has been developed. However, despite its effectiveness for long-lasting and large occlusions, this approach tends to fail whenever the person is monitored with multiple cameras and he appears in one of them already occluded. 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.
5th International Conference on Methods and Techniques in Behavioral Research
Wageningen, The Netherlands
30 August - 2 September 2005
1
172
175
Cucchiara, Rita; Prati, Andrea; Vezzani, Roberto
Making the home safer and more secure through visual surveillance / Cucchiara, Rita; Prati, Andrea; Vezzani, Roberto. - STAMPA. - 1:(2005), pp. 172-175. ((Intervento presentato al convegno 5th International Conference on Methods and Techniques in Behavioral Research tenutosi a Wageningen, The Netherlands nel 30 August - 2 September 2005.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/466439
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