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A Pipelined Real-Time Optical Flow Algorithm

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Image Analysis and Recognition (ICIAR 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3212))

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Abstract

Optical flow algorithms generally demand for high computational power and huge storage capacities. This paper is a contribution for real-time implementation of an optical flow algorithm on a pipeline machine. This overall optical flow computation methodology is presented and evaluated on a set of synthetic and real image sequences. Results are compared to other implementations using as measures the average angular error, the optical flow density and the root mean square error. The proposed implementation achieves very low computation delays, allowing operation at standard video frame-rate and resolution. It compares favorably to recent implementations in standard microprocessors and in parallel hardware.

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Author information

Authors and Affiliations

  1. Instituto de Engenharia Biomédica, Laboratório de Sinal e Imagem Biomédica,  

    Miguel V. Correia & Aurélio Campilho

  2. Fac. Engenharia, Dept. Eng. Electrotécnica e Computadores, Universidade do Porto, Rua Dr. Roberto Frias, s/n, 4200–465, Porto, Portugal

    Miguel V. Correia & Aurélio Campilho

Authors
  1. Miguel V. Correia
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  2. Aurélio Campilho
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Editor information

Editors and Affiliations

  1. FEUP - Faculdade de Engenharia, Universidade do Porto, Rua Dr. Roberto Frias, 4200-465, Porto, Portugal

    Aurélio Campilho

  2. Electrical and Computer Engineering Department, University of Waterloo,  

    Mohamed Kamel

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© 2004 Springer-Verlag Berlin Heidelberg

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Correia, M.V., Campilho, A. (2004). A Pipelined Real-Time Optical Flow Algorithm. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2004. Lecture Notes in Computer Science, vol 3212. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30126-4_46

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  • DOI: https://doi.org/10.1007/978-3-540-30126-4_46

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23240-7

  • Online ISBN: 978-3-540-30126-4

  • eBook Packages: Springer Book Archive

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