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International Conference on Advanced Concepts for Intelligent Vision Systems

ACIVS 2007: Advanced Concepts for Intelligent Vision Systems pp 285–296Cite as

Patch-Based Experiments with Object Classification in Video Surveillance

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 4678))

Abstract

We present a patch-based algorithm for the purpose of object classification in video surveillance. Within detected regions-of-interest (ROIs) of moving objects in the scene, a feature vector is calculated based on template matching of a large set of image patches. Instead of matching direct image pixels, we use Gabor-filtered versions of the input image at several scales. This approach has been adopted from recent experiments in generic object-recognition tasks. We present results for a new typical video surveillance dataset containing over 9,000 object images. Furthermore, we compare our system performance with another existing smaller surveillance dataset. We have found that with 50 training samples or higher, our detection rate is on the average above 95%. Because of the inherent scalability of the algorithm, an embedded system implementation is well within reach.

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Author information

Authors and Affiliations

  1. Bosch Security Systems B.V., Glaslaan 2, Eindhoven, The Netherlands

    Rob Wijnhoven

  2. Technische Universiteit Eindhoven, Eindhoven, The Netherlands

    Rob Wijnhoven & Peter H. N. de With

  3. LogicaCMG, Tech. Softw. Eng., Eindhoven, The Netherlands

    Peter H. N. de With

Authors
  1. Rob Wijnhoven
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  2. Peter H. N. de With
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Editor information

Jacques Blanc-Talon Wilfried Philips Dan Popescu Paul Scheunders

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© 2007 Springer-Verlag Berlin Heidelberg

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Wijnhoven, R., de With, P.H.N. (2007). Patch-Based Experiments with Object Classification in Video Surveillance. In: Blanc-Talon, J., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2007. Lecture Notes in Computer Science, vol 4678. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74607-2_26

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  • DOI: https://doi.org/10.1007/978-3-540-74607-2_26

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-74606-5

  • Online ISBN: 978-3-540-74607-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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