http://www.cnr.it/ontology/cnr/individuo/prodotto/ID52519

A Supervised Approach in Background Modelling for Visual Surveillance (Articolo in rivista)

Type

Label

A Supervised Approach in Background Modelling for Visual Surveillance (Articolo in rivista) (literal)

Anno

Alternative label

Leo M., Spagnolo P., Attolico G., Distante A. (2003)
A Supervised Approach in Background Modelling for Visual Surveillance
in Lecture notes in computer science
(literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori

Pagina inizio

Pagina fine

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#altreInformazioni

The product is published in Lecture Notes in Computer Science (LNCS) which commenced publication in 1973. It has established itself as a medium for the publication of new developments in computer science and information technology research and teaching - quickly, informally, and at a high level. The cornerstone of LNCS's editorial policy is its unwavering commitment to report the latest results from all areas of computer science and information technology research, development, and education. LNCS has always enjoyed close cooperation with the computer science R & D community, with numerous renowned academics, and with prestigious institutes and learned societies. (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume

Rivista

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#descrizioneSinteticaDelProdotto

This journal publication deals with the problem of motion detection and object segmentation in outdoor environments. This is a fundamental and challenging step in many application domains, first of all in a video surveillance context. The possibility to update areas of the background covered by foreground objects and to manage small and repetitive movements of the vegetation are the main novelties of the paper with respect the related works in the open literature. This study and its satisfactory results have been the first step towards the design and implementation of an automatic surveillance system able to recognize moving object, to track human being and finally to monitor their activities in an archaeological site in order to detect illegal behaviors as thefts or vandalic actions. (literal)

Note

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni

Titolo

Abstract

In this paper we address the context of visual surveillance in outdoor environments involving the detection of moving objects in the observed scene. In particular, a reliable foreground segmentation, based on a background subtraction approach, is explored. We firstly address the problem arising when small movements of background objects, as trees blowing in the wind, generate false alarms. We propose a background model that uses a supervised training for coping with these situations. In addition, in real outdoor scenes the continuous variations of lighting conditions determine unexpected intensity variations in the background model parameters. We propose a background updating algorithm that work on all the pixels in the background image, even if covered by a foreground object. The experiments have been performed on real image sequences acquired in a real archaeological site. (literal)

Prodotto di