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Low Complexity Corner Detector Using CUDA for Multimedia Applications

Rajat Phull, Pradip Mainali, Qiong Yang, Patrice Rondao Alface, Henk Sips
Interuniversitair Micro-Electronica Centrum vzw., Interdisciplinary Institute for BroadBand Technology, Kapeldreef 75, Leuven B-3001, Belgium
Third International Conferences on Advances in Multimedia (MMEDIA), 2011

@inproceedings{rondao2011low,

   title={Low Complexity Corner Detector Using CUDA for Multimedia Applications},

   author={Rondao Alface, P.},

   booktitle={MMEDIA 2011, The Third International Conferences on Advances in Multimedia},

   pages={7–11},

   year={2011}

}

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High speed feature detection is a requirement for many real-time multimedia and computer vision applications. In previous work, the Harris and KLT algorithms were redesigned to increase the performance by reducing the algorithmic complexity, resulting in the Low Complexity Corner Detector algorithm. To attain further speedup, this paper proposes the implementation of this low complexity corner detector algorithm on a parallel computing architecture, namely a GPU using Compute Unified Device Architecture (CUDA). We show that the low complexity corner detector is 2-3 times faster than the Harris corner detector algorithm on the same GPU platform.
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