Efficient Integral Image Computation on the GPU
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Horn_Efficient integral.pdf
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721.29 KB
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Adobe PDF
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Author(s)
Bilgic, Berkin
Horn, Berthold Klaus Paul
Masaki, Ichiro
Date Issued
June 2010
Journal
2010 IEEE Intelligent Vehicles Symposium (IV)
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Bilgic, B, B K P Horn, and I Masaki. “Efficient Integral Image Computation on the GPU.” IEEE, 2010. 528–533. © Copyright 2010 IEEE
Version
Final published version
Abstract
We present an integral image algorithm that can run in real-time on a Graphics Processing Unit (GPU). Our system exploits the parallelisms in computation via the NIVIDA CUDA programming model, which is a software platform for solving non-graphics problems in a massively parallel high-performance fashion. This implementation makes use of the work-efficient scan algorithm that is explicated in. Treating the rows and the columns of the target image as independent input arrays for the scan algorithm, our method manages to expose a second level of parallelism in the problem. We compare the performance of the parallel approach running on the GPU with the sequential CPU implementation across a range of image sizes and report a speed up by a factor of 8 for a 4 megapixel input. We further investigate the impact of using packed vector type data on the performance, as well as the effect of double precision arithmetic on the GPU.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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DOI of Published Version
https://doi.org/10.1109/IVS.2010.5548142
