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Background Subtraction Techniques: Systematic Evaluation and Comparative Analysis

  • Conference paper
Advanced Concepts for Intelligent Vision Systems (ACIVS 2009)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5807))

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Abstract

Moving object detection is a critical task for many computer vision applications: the objective is the classification of the pixels in the video sequence into either foreground or background. A commonly used technique to achieve it in scenes captured by a static camera is Background Subtraction (BGS). Several BGS techniques have been proposed in the literature but a rigorous comparison that analyzes the different parameter configuration for each technique in different scenarios with precise ground-truth data is still lacking. In this sense, we have implemented and evaluated the most relevant BGS techniques, and performed a quantitative and qualitative comparison between them.

Work supported by the Spanish Government (TEC2007-65400 – SemanticVideo), the Spanish Administration agency CDTI (CENIT-VISION 2007-1007) and the Comunidad de Madrid (S-0505/TIC-0223 - ProMultiDis-CM).

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Author information

Authors and Affiliations

  1. Video Processing and Understanding Lab (VPULab), Universidad Autónoma de Madrid, E-28049, Madrid, Spain

    Sonsoles Herrero & Jesús Bescós

Authors
  1. Sonsoles Herrero
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  2. Jesús Bescós
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Editor information

Editors and Affiliations

  1. DGA/D4S/MRIS, CEP/GIP, 16 bis avenue Prieur de la côte d’or., 94114, Arcueil, France

    Jacques Blanc-Talon

  2. Department of Telecommunication and Information Processing, Ghent University, St.-Pietersnieuwstraat 41, 9000, Gent, Belgium

    Wilfried Philips

  3. CSIRO ICT Centre, Epping, Po Box 76, 1710, Sydney, NSW, Australia

    Dan Popescu

  4. University of Antwerp, Universiteitsplein 1; Building N., 2610, Wilrijk, Belgium

    Paul Scheunders

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© 2009 Springer-Verlag Berlin Heidelberg

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Herrero, S., Bescós, J. (2009). Background Subtraction Techniques: Systematic Evaluation and Comparative Analysis. In: Blanc-Talon, J., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2009. Lecture Notes in Computer Science, vol 5807. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04697-1_4

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  • DOI: https://doi.org/10.1007/978-3-642-04697-1_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-04696-4

  • Online ISBN: 978-3-642-04697-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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