Parallelization Techniques for Spatial-Temporal Occupancy Maps from Multiple Video Streams

  • Nathan DeBardeleben
  • Adam Hoover
  • William Jones
  • Walter Ligon
Conference paper

DOI: 10.1007/3-540-45591-4_27

Part of the Lecture Notes in Computer Science book series (LNCS, volume 1800)
Cite this paper as:
DeBardeleben N., Hoover A., Jones W., Ligon W. (2000) Parallelization Techniques for Spatial-Temporal Occupancy Maps from Multiple Video Streams. In: Rolim J. (eds) Parallel and Distributed Processing. IPDPS 2000. Lecture Notes in Computer Science, vol 1800. Springer, Berlin, Heidelberg

Abstract

We describe and analyze several techniques to parallelize a novel algorithm that fuses intensity data from multiple video cameras to create a spatial-temporal occupancy map. Instead of tracking objects, the algorithm operates by recognizing free space. The brevity of operations in the algorithm allows a dense spatial occupancy map to be temporally computed at real-time video rates. Since each input image pixel is processed independently, we demonstrate parallel implementations that achieve nearly ideal speedup on a four processor shared memory architecture. Potential applications include surveillance, robotics, virtual reality, and manufacturing environments.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • Nathan DeBardeleben
    • 1
  • Adam Hoover
    • 1
  • William Jones
    • 1
  • Walter Ligon
    • 1
  1. 1.Parallel Architecture Research LaboratoryClemson UniversityClemson

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