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Overview of approaches for accelerating scale invariant feature detection algorithm

Jing Zhang, Hongshi Sang, Xubang Shen
National Key Laboratory of Science and Technology on Multi-spectral Information Processing, Institute for Pattern Recognition & Artificial Intelligence, Huazhong University of Science & Technology, Wuhan, 430074, China
International Conference on Electric Information and Control Engineering (ICEICE), 2011

@inproceedings{sang2011overview,

   title={Overview of approaches for accelerating scale invariant feature detection algorithm},

   author={Sang, H. and Shen, X.},

   booktitle={Electric Information and Control Engineering (ICEICE), 2011 International Conference on},

   pages={585–589},

   organization={IEEE},

   year={2011}

}

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SIFT (Scale Invariant Feature Transform) is one of most popular approach for feature detection and matching. Many parallelized algorithms have been proposed to accelerate SIFT to apply into real-time systems. This paper divides the researches into three different categories, that is, optimizing parallel algorithms based on general purpose multi-core processors, designing customized multi-core processor dedicated for SIFT and implementing SIFT based FPGA (Field Programmable Gate Arrays). Overview of the three type researches and analysis of task-level parallelism are presented in this paper.
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