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Real-Time Image-Based Motion Detection Using Color and Structure

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Image Analysis and Recognition (ICIAR 2009)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5627))

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Abstract

In this paper we propose a method for automating the process of detecting regions of motion in a video sequence in real time. The main idea of this work is to detect motion based on both structure and color. The detection using structure is carried out with the aid of information gathered from the Census Transform computed on gradient images based on Sobel operators. The Census Transform characterizes local intensity patterns in an image region. Color-based detection is done using color histograms, which allow efficient characterization without prior assumptions about color distribution in the scene. The probabilities obtained from the gradient-based Census Transform and from Color Histograms are combined in a robust way to detect the zones of active motion. Experimental results demonstrate the effectiveness of our approach.

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Author information

Authors and Affiliations

  1. Computer Science Department, University of Texas at El Paso, 500 West University Avenue, El Paso, TX, 79968

    Manali Chakraborty & Olac Fuentes

Authors
  1. Manali Chakraborty
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  2. Olac Fuentes
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Editor information

Editors and Affiliations

  1. Department of Electrical and Computer Engineering, University of Waterloo, N2L 3G1, Waterloo, Ontario, Canada

    Mohamed Kamel

  2. Faculty of Engineering, Institute of Biomedical Engineering, University of Porto, Rua Dr. Roberto Frias, 4200-465, Porto, Portugal

    Aurélio Campilho

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Chakraborty, M., Fuentes, O. (2009). Real-Time Image-Based Motion Detection Using Color and Structure. In: Kamel, M., Campilho, A. (eds) Image Analysis and Recognition. ICIAR 2009. Lecture Notes in Computer Science, vol 5627. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02611-9_67

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  • DOI: https://doi.org/10.1007/978-3-642-02611-9_67

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-02610-2

  • Online ISBN: 978-3-642-02611-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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