Overview of approaches for accelerating scale invariant feature detection algorithm
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}
}
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.
June 30, 2011 by hgpu
