NDLI: Comparative Evaluation of Stationary Foreground Object Detection Algorithms Based on Background Subtraction Techniques

Content Provider	IEEE Xplore Digital Library
Author	Bayona, A. SanMiguel, J.C. Martinez, J.M.
Copyright Year	2009
Abstract	In several video surveillance applications, such as the detection of abandoned/stolen objects or parked vehicles,the detection of stationary foreground objects is a critical task. In the literature, many algorithms have been proposed that deal with the detection of stationary foreground objects, the majority of them based on background subtraction techniques. In this paper we discuss various stationary object detection approaches comparing them in typical surveillance scenarios (extracted from standard datasets). Firstly, the existing approaches based on background-subtraction are organized into categories. Then, a representative technique of each category is selected and described. Finally, a comparative evaluation using objective and subjective criteria is performed on video surveillance sequences selected from the PETS 2006 and i-LIDS forAVSS 2007 datasets, analyzing the advantages and drawbacks of each selected approach.
Starting Page	25
Ending Page	30
File Size	316343
Page Count	6
File Format	PDF
ISBN	9781424447558
DOI	10.1109/AVSS.2009.35
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-09-02
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Performance evaluation Subtraction techniques Intelligent vehicles Vehicle detection Layout Object detection Signal processing Video surveillance Cameras Positron emission tomography
Content Type	Text
Resource Type	Article

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