Abstract

In the last years, smart surveillance has been one of the most active research topics in computervision because of the wide spectrum of promising applications. Its main point is about the use of automatic videoanalysis technologies for surveillance purposes. In general, a processing framework for smart surveillanceconsists of a preliminary motion detection step in combination with high-level reasoning that allows automaticunderstanding of evolutions of observed scenes. In this paper, we propose a surveillance framework based on aset of reliable visual algorithms that perform different tasks: a motion analysis approach that segmentsforeground regions is followed by three procedures, which perform object tracking, homographic transformationsand edge matching, in order to achieve the real-time monitoring of forbidden areas and the detection ofabandoned or removed objects. Several experiments have been performed on different real image sequencesacquired from a Messapic museum (indoor context) and the nearby archaeological site (outdoor context) todemonstrate the effectiveness and the flexibility of the proposed approach.

Autore Pugliese

• Leo Marco , Spagnolo Paolo , Mazzeo Pier Luigi , D'orazio Tiziana Rita

Tutti gli autori

• M. Leo; P.Spagnolo; P.L.Mazzeo;T.D'Orazio;A.Distante

Titolo volume/Rivista

Expert systems

Anno di pubblicazione

2010

ISSN

0266-4720

ISBN

Non Disponibile

Numero di citazioni Wos

Nessuna citazione

Ultimo Aggiornamento Citazioni

Non Disponibile

Numero di citazioni Scopus

Non Disponibile

Ultimo Aggiornamento Citazioni

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Settori ERC

Non Disponibile

Codici ASJC

Non Disponibile