TAILIEUCHUNG - Báo cáo sinh học: " Research Article An Experimental Evaluation of Foreground Detection Algorithms in Real Scenes"

Tuyển tập các báo cáo nghiên cứu về sinh học được đăng trên tạp chí sinh học Journal of Biology đề tài: Research Article An Experimental Evaluation of Foreground Detection Algorithms in Real Scenes | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2010 Article ID 373941 11 pages doi 2010 373941 Research Article An Experimental Evaluation of Foreground Detection Algorithms in Real Scenes Donatello Conte Pasquale Foggia Gennaro Percannella Francesco Tufano and Mario Vento Dipartimento di Ingegneria deirinformazione ed Ingegneria Elettrica Universita di Salerno Via Ponte don Melillo 84084 Fisciano Italy Correspondence should be addressed to Donatello Conte dconte@ Received 15 December 2009 Revised 18 March 2010 Accepted 11 May 2010 Academic Editor ChangIck Kim Copyright 2010 Donatello Conte et al. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. Foreground detection is an important preliminary step of many video analysis systems. Many algorithms have been proposed in the last years but there is not yet a consensus on which approach is the most effective not even limiting the problem to a single category of videos. This paper aims at constituting a first step towards a reliable assessment of the most commonly used approaches. In particular four notable algorithms that perform foreground detection have been evaluated using quantitative measures to assess their relative merits and demerits. The evaluation has been carried out using a large publicly available dataset composed by videos representing different realistic applicative scenarios. The obtained performance is presented and discussed highlighting the conditions under which algorithm can represent the most effective solution. 1. Introduction Several video analysis applications like intelligent video surveillance or vehicular traffic analysis require as a preliminary subtask the identification within the scene of the moving objects foreground of the scene as opposed to the static parts of the scene

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