Detecting moving objects, ghosts, and shadows in video streams

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Show simple item record Grana Costantino en_US Piccardi Massimo en_US Cucchiara Rita en_US Prati Andrea en_US 2009-12-21T03:52:36Z 2009-12-21T03:52:36Z 2003 en_US
dc.identifier 2003000355 en_US
dc.identifier.citation Cucchiara Rita et al. 2003, 'Detecting moving objects, ghosts, and shadows in video streams', IEEE Computer Soc, vol. 25, no. 10, pp. 1337-1342. en_US
dc.identifier.issn 0162-8828 en_US
dc.identifier.other C1 en_US
dc.description.abstract Background subtraction methods are widely exploited for moving object detection in videos in many applications, such as traffic monitoring, human motion capture, and video surveillance. How to correctly and efficiently model and update the background model and how to deal with shadows are two of the most distinguishing and challenging aspects of such approaches. This work proposes a general-purpose method that combines statistical assumptions with the object level knowledge of moving objects, apparent objects (ghosts), and shadows acquired in the processing of the previous frames. Pixels belonging to moving objects, ghosts, and shadows are processed differently in order to supply an object-based selective update. The proposed approach exploits color information for both background subtraction and shadow detection to improve object segmentation and background update. The approach proves fast, flexible, and precise in terms of both pixel accuracy and reactivity to background changes. en_US
dc.publisher Institute of Electrical and Electronics Engineers en_US
dc.relation.hasversion Accepted manuscript version en_US
dc.relation.isbasedon en_US
dc.title Detecting moving objects, ghosts, and shadows in video streams en_US
dc.parent IEEE Transactions On Pattern Analysis And Machine Intelligence en_US
dc.journal.volume 25 en_US
dc.journal.number 10 en_US
dc.publocation Piscataway, USA en_US
dc.identifier.startpage 1337 en_US
dc.identifier.endpage 1342 en_US Information Technology en_US

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