[1] Lowe D G. Distinctive image features from scale-invariant keypoints[J]. International Journal of Computer Vision, 60, 91-110(2004). http://doi.ieeecomputersociety.org/resolve?ref_id=doi:10.1023/B:VISI.0000029664.99615.94&rfr_id=trans/tp/2008/10/ttp2008101683.htm

[2] Deng B S[J]. An improved algorithm of the screen space ambient occlusion Modern Computer, 2017, 54-57.

[3] Fu W P, Qin C, Liu J et al. Matching and location of image object based on SIFT algorithm[J]. Chinese Journal of Scientific Instrument, 32, 163-169(2011).

[4] Pang R, Xu C R. Parallel implementation and optimization of remote sensing image matching based on SIFT feature[J]. Journal of Jiangxi University of Science and Technology, 37, 28-33(2016).

[5] Wang B L, Zhu Z L, Meng L. CUDA-based acceleration algorithm of SIFT feature extraction[J]. Journal of Northeastern University(Natural Science), 34, 200-204(2013).

[6] Zhao P, Yan M, Li S K. Performance optimization of application algorithms for heterogeneous multi-processor system-on-chips[J]. Journal of Software, 22, 1475-1487(2011).

[7] Feng Y, Yuan Q H, Shen J W. Study on programming mothods based on CPU+GPU hybird computing[J]. Communications Technology, 44, 141-143(2011).

[8] Jiang C, Geng Z X, Lou B et al. Parallel processing research on SIFT feature matching algorithm based on GPU[J]. Computer Science, 40, 295-297, 307(2013).

[9] Jiang L Y. Research on image matching functions performance optimization using OpenCL[D]. Beijing: University of Chinese Academy of Sciences, 23-35(2013).

[10] Peng X X. Research on parallel accelerating algorithm based on OpenCL and realization on FPGA[D]. Wuhan: Wuhan Institute of Technology, 17-27(2014).

[11] Xiao H, Guo Y H, Zhou Q L. Parallel algorithm of CPU and GPU-oriented heterogeneous computation in SIFT feature matching[J]. Journal of Tongji University(Natural Science), 41, 1732-1737(2013).

[12] Xu C P, Wang G. Parallel design and implementation of scale invariant feature transform algorithm based on OpenCL[J]. Journal of Computer Applications, 36, 1801-1806(2016).

[13] Li Q, Yin Y A. Research on ranging system and stereo matching algorithm based on binocular camera[J]. Telecom Power Technology, 33, 66-67(2016).

[14] Li S X. A method and experiment for measuring distance of object parallax from image[D]. Beijing: Beijing Institute of Technology, 21-26(2015).

[15] Wang D D. Research and application of the method to distance measurement based on binocular vision[D]. Chongqing: Chongqing University of Technology, 37-41(2016).

[16] Sun J G, Liu J, Zhao L Y. Clustering algorithms research[J]. Journal of Software, 19, 48-61(2008).

[17] Shao N, Li H G, Liu L. Binocular stereo distance-measurement method based on feature matching algorithm[J]. Journal of Yanshan University, 36, 57-61(2012).

[18] Zhang X, Jin Y X, Xue D. Image matching algorithm based on SICA-SIFT and particle swarm optimization[J]. Laser & Optoelectronics Progress, 54, 091002(2017).

[19] Jiang X D, Yu J Y, Zhu L K et al. Self-calibrated binocular ranging system based on hardware SURF algorithm[J]. Acta Optica Sinica, 38, 1036001(2018).

[20] Yuan R F, Liu M, Hui M et al. Depth map stitching based on binocular vision[J]. Laser & Optoelectronics Progress, 55, 121013(2018).

[21] Liu Y Y, Feng P, Long Z R et al. Research and implementation of binocular location system based on region of interest segmentation[J]. Laser & Optoelectronics Progress, 55, 051102(2018).

[22] de Arruda G F, da Fontoura Costa L, Rodrigues F A. A complex networks approach for data clustering[J]. Physica A: Statistical Mechanics and its Applications, 391, 6174-6183(2012).

[23] Zhan Z F. Research of SIFT stereo matching algorithm based on GPU[D]. Harbin: Harbin Institute of Technology, 53-61(2014).