In this paper we propose an approach to indoor environment surveillance and, in particular, to people behaviour control in home automation context. The reference application is a silent and automatic control of the behaviour of people living alone in the house and specially conceived for people with limited autonomy (e.g., elders or disabled people). The aim is to detect dangerous events (such as a person falling down) and to react to these events by establishing a remote connection with low-performance clients, such as PDA (Personal Digital Assistant). To this aim, we propose an integrated server architecture, typically connected in intranet with network cameras, able to segment and track objects of interest; in the case of objects classified as people, the system must also evaluate the people posture and infer possible dangerous situations. Finally, the system is equipped with a specifically designed transcoding server to adapt the video content to PDA requirements (display area and bandwidth) and to the user's requests. The main issues of the proposal are a reliable real-time object detector and tracking module, a simple but effective posture classifier improved by a supervised learning phase, and an high performance transcoding inspired on MPEG-4 object-level standard, tailored to PDA. Results on different video sequences and performance analysis are discussed.

Computer Vision Techniques for PDA Accessibility of In-House Video Surveillance / Cucchiara, Rita; Grana, Costantino; A., Prati; Vezzani, Roberto. - STAMPA. - (2003), pp. 87-97. ((Intervento presentato al convegno First ACM SIGMM international workshop on Video surveillance tenutosi a Berkeley, California nel Nov 2-8.

Computer Vision Techniques for PDA Accessibility of In-House Video Surveillance

CUCCHIARA, Rita;GRANA, Costantino;VEZZANI, Roberto
2003-01-01

Abstract

In this paper we propose an approach to indoor environment surveillance and, in particular, to people behaviour control in home automation context. The reference application is a silent and automatic control of the behaviour of people living alone in the house and specially conceived for people with limited autonomy (e.g., elders or disabled people). The aim is to detect dangerous events (such as a person falling down) and to react to these events by establishing a remote connection with low-performance clients, such as PDA (Personal Digital Assistant). To this aim, we propose an integrated server architecture, typically connected in intranet with network cameras, able to segment and track objects of interest; in the case of objects classified as people, the system must also evaluate the people posture and infer possible dangerous situations. Finally, the system is equipped with a specifically designed transcoding server to adapt the video content to PDA requirements (display area and bandwidth) and to the user's requests. The main issues of the proposal are a reliable real-time object detector and tracking module, a simple but effective posture classifier improved by a supervised learning phase, and an high performance transcoding inspired on MPEG-4 object-level standard, tailored to PDA. Results on different video sequences and performance analysis are discussed.
First ACM SIGMM international workshop on Video surveillance
Berkeley, California
Nov 2-8
87
97
Cucchiara, Rita; Grana, Costantino; A., Prati; Vezzani, Roberto
Computer Vision Techniques for PDA Accessibility of In-House Video Surveillance / Cucchiara, Rita; Grana, Costantino; A., Prati; Vezzani, Roberto. - STAMPA. - (2003), pp. 87-97. ((Intervento presentato al convegno First ACM SIGMM international workshop on Video surveillance tenutosi a Berkeley, California nel Nov 2-8.
File in questo prodotto:
Non ci sono file associati a questo prodotto.
Pubblicazioni consigliate

Caricamento pubblicazioni consigliate

Licenza Creative Commons
I metadati presenti in IRIS UNIMORE sono rilasciati con licenza Creative Commons CC0 1.0 Universal, mentre i file delle pubblicazioni sono rilasciati con licenza Attribuzione 4.0 Internazionale (CC BY 4.0), salvo diversa indicazione.
In caso di violazione di copyright, contattare Supporto Iris

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/466426
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 25
  • ???jsp.display-item.citation.isi??? ND
social impact