Parallelization Techniques for Spatial-Temporal Occupancy Maps from Multiple Video Streams
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.
- A. Hoover and B. Olsen, “A Real-Time Occupancy Map from Multiple Video Streams”, in IEEE IGRA, 1999, pp. 2261–2266.
- D. Patterson and J. Hennessy, Computer Architecture: A Quantitative Approach, second edition, Morgan Kaufmann, 1996.
- Parallelization Techniques for Spatial-Temporal Occupancy Maps from Multiple Video Streams
- Book Title
- Parallel and Distributed Processing
- Book Subtitle
- 15 IPDPS 2000 Workshops Cancun, Mexico, May 1–5, 2000 Proceedings
- pp 202-209
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- Series Title
- Lecture Notes in Computer Science
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- Springer Berlin Heidelberg
- Copyright Holder
- Springer-Verlag Berlin Heidelberg
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