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Speeding Up Computer Vision Applications on Mobile Computing Platforms

Luna Backes
Universitat Politecnica de Catalunya (UPC) – BarcelonaTech, Facultat d’Informatica de Barcelona (FIB)
Universitat Politecnica de Catalunya, 2015

@article{backes2015speeding,

   title={Speeding up computer vision applications on mobile computing platforms},

   author={Backes Drault, Luna},

   year={2015},

   publisher={Universitat Polit{‘e}cnica de Catalunya}

}

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Computer vision (CV) is widely expected to be the next "Big Thing" in mobile computing. For example, Google has recently announced their project "Tango", a 5-inch Android phone containing highly customized hardware and software designed to track the full 3-dimensional motion of the device as you hold it while simultaneously creating a map of the environment. One of the problems yet to solve is how to transfer demanding state-of-the-art computer vision algorithms -designed to run on powerful desktop computers with several graphics processing units (GPUs) – onto energy-efficient, but slow embedded GPUs found in mobile devices. This project investigates ways of speeding up computer vision kernels and applications through optimisation and parallelisation. We took a representative example of a CV application, the KinectFusion, and we ported it to a mobile platform using OpenCL. Then, we conducted a performance evaluation, identifying performance bottlenecks and further optimise performance. We finally broaden our focus and studied its performance on a different platform to evaluate the performance portability of our optimisations.
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