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Novel Applications of Intelligent Systems pp 123–138Cite as

ARTOD: Autonomous Real Time Objects Detection by a Moving Camera Using Recursive Density Estimation

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 586))

Abstract

A new approach to autonomously detect moving objects in a video captured by a moving camera is proposed in this chapter. The proposed method is separated in two modules. In the first part, the well-known scale invariant feature transformation (SIFT) and the RANSAC algorithm are used to estimate the camera movement. In the second part, recursive density estimation (RDE) is used to build a model of the background and detect moving objects in a scene. The results are presented for both indoor and outdoor video sequences taken from a UAV for outdoor scenario and handheld camera for indoor experiment.

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Author information

Authors and Affiliations

  1. School of Computing and Communications, Infolab21, Lancaster University, City of Lancaster, LA1 4WA, UK

    Pouria Sadeghi-Tehran & Plamen Angelov

Authors
  1. Pouria Sadeghi-Tehran
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  2. Plamen Angelov
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Corresponding author

Correspondence to Plamen Angelov .

Editor information

Editors and Affiliations

  1. Institute of Information and Communication Technologies, Bulgarian Academy of Sciences, Sofia, Bulgaria

    Mincho Hadjiski

  2. KEDRI – Knowledge Engineering and Discovery Research Institute, Auckland University of Technology, Auckland, New Zealand

    Nikola Kasabov

  3. Research & Advanced Engineering, Ford Motor Company, Dearborn, Michigan, USA

    Dimitar Filev

  4. University of Library Studies and Information Technologies, Sofia, Bulgaria

    Vladimir Jotsov

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© 2016 Springer International Publishing Switzerland

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Sadeghi-Tehran, P., Angelov, P. (2016). ARTOD: Autonomous Real Time Objects Detection by a Moving Camera Using Recursive Density Estimation. In: Hadjiski, M., Kasabov, N., Filev, D., Jotsov, V. (eds) Novel Applications of Intelligent Systems. Studies in Computational Intelligence, vol 586. Springer, Cham. https://doi.org/10.1007/978-3-319-14194-7_7

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  • DOI: https://doi.org/10.1007/978-3-319-14194-7_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-14193-0

  • Online ISBN: 978-3-319-14194-7

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