A Multi-sensor approach for People Fall Detection in Home Environment (Contributo in atti di convegno)

Type
Label
  • A Multi-sensor approach for People Fall Detection in Home Environment (Contributo in atti di convegno) (literal)
Anno
  • 2008-01-01T00:00:00+01:00 (literal)
Alternative label
  • A. Leone, G. Diraco, C. Distante, P.Siciliano, M. Malfatti, L. Gonzo, M. Grassi, A. Lombardi, G. Rescio, P. Malcovati, V. Libal, J. Huang, G. Potamianos (2008)
    A Multi-sensor approach for People Fall Detection in Home Environment
    in 10th European Conference on Computer Vision (ECCV2008), Marseille, 1-6 Oct 2008
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • A. Leone, G. Diraco, C. Distante, P.Siciliano, M. Malfatti, L. Gonzo, M. Grassi, A. Lombardi, G. Rescio, P. Malcovati, V. Libal, J. Huang, G. Potamianos (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#titoloVolume
  • Workshop on Multi-camera and Multi-modal Sensor Fusion Algorithms and Applications (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • CNR (literal)
Titolo
  • A Multi-sensor approach for People Fall Detection in Home Environment (literal)
Abstract
  • This paper presents a hardware and software framework for reliable fall detection in the home environment, with particular focus on the protection and assistance to the elderly. The integrated proto- type includes three different sensors: a 3D Time-Of-Flight range camera, a wearable MEMS accelerometer and a microphone. These devices are connected with custom interface circuits to a central PC that collects and processes the information with a multi-threading approach. For each of the three sensors, an optimized algorithm for fall-detection has been developed and benchmarked on a collected mulitimodal database. This work is expected to lead to a multi-sensory approach employing appro- priate fusion techniques aiming to improve system precision and recall. (literal)
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