Computer Science ›› 2016, Vol. 43 ›› Issue (Z6): 165-167.doi: 10.11896/j.issn.1002-137X.2016.6A.038

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SIFT Feature Extraction Parallel Algorithm on Mobile Device

GAN Wei, ZHANG Su-wen, LEI Zhen and LI Yi-fan   

  • Online:2018-12-01 Published:2018-12-01

Abstract: Feature extraction and matching is an important part in computervision applications,such as image matching,object recognition and video tracking.SIFT algorithm is widely used in the field of image registration because of its scale invariance and rotation invariance.To deal with the low efficiency of the traditional SIFT algorithm,we proposed an efficient method which is implemented on mobile platform.In this paper,we used the OpenCL to achieve the SIFT algorithm on mobile device,through redistributing the calculation of tasks and optimizing the SIFT algorithm in the mobile OpenCL parallel implementation.Experimental results show that our SIFT algorithm takes full advantage of the GPU parallel computing power,greatly improving the efficiency of the SIFT algorithm,achieving the efficient feature extraction.

Key words: SIFT,OpenCL,GPU,Feature extraction

[1] Lowe D G.Distinctive Image Features from Scale-Invariant Keypoints[J].International Journal of Computer Vision,2004,60(2):91-110
[2] Sinha S N,Frahm J M,Pollefeys M,et al.Feature tracking and matching in video using programmable graphics hardware[J].Machine Vision & Applications,2011,22(1):207-217
[3] Kayombya G R.SIFT feature extraction on a Smartphone GPU using OpenGL ES2.0[D].Massachusetts:Massachusetts Institute of Technology,2011
[4] Rister B,Wang G,Wu M,et al.A fast and efficient sift detector using the mobile GPU[C]∥2013 IEEE International Confe-rence on Acoustics,Speech and Signal Processing (ICASSP).IEEE,2013:2674-2678
[5] Wang Wei-yan,Zhang Yun-quan,Long Guo-ping,et al.CLSIFT:An Optimization Study of the Scale Invariant Feature Transform on GPUs[C]∥IEEE 15th International Conference on High Performance Computing and Communication.2013
[6] Wang G,Rister B,Cavallaro J R.Workload Analysis and Efficient OpenCL-based Implementation of SIFT Algorithm on a Smartphone[C]∥ Global Conference on Signal and Information Processing(GlobalSIP).IEEE,2013:759-762
[7] Wang G.An easy-to use standalone SIFT library easy-to-usestandalone SIFT library written in C/C++[CP/OL].http://sourceforge.net/projects/ezsift
[8] 张樱,张云泉,龙国平.基于OpenCL的图像模糊化算法优化研究[J].计算机科学,2012,39(3):260-264
[9] 贾海鹏,张云泉,徐建良.基于OpenCL的图像积分图算法优化研究[J].计算机科学,2013,0(2):1-7
[10] 王瑞,梁华,蔡宣平.基于GPU的SIFT特征提取算法研究[J].现代电子技术,2010,33(15):41-43

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