[1] 新华网.上海外滩踩踏事件[EB/OL].[2018-03-26]. http://www.xinhuanet.com/politics/szjcxzt/shwtctsg/. (Xinhuanet. Shanghai bund stampede[EB/OL].[2018-03-26]. http://www.xinhuanet.com/politics/szjcxzt/shwtctsg/.) [2] 张君军,石志广,李吉成.人数统计与人群密度估计技术研究现状与趋势[J].计算机工程与科学,2018,40(2):282-291.(ZHANG J J, SHI Z G, LI J C. Current researches and future perspectives of crowd counting and crowd density estimation technology[J]. Computer Engineering and Science, 2018, 40(2):282-291.) [3] GE W N, COLLINS R T. Marked point processes for crowd counting[C]//Proceedings of the 2009 IEEE Conference on Computer Vision and Pattern Recognition. Washington, DC:IEEE Computer Society, 2009:2913-2920. [4] BROSTOW G J, CIPOLLA R. Unsupervised Bayesian detection of independent motion in crowds[C]//Proceedings of the 2006 IEEE Conference on Computer Vision and Pattern Recognition. Piscataway, NJ:IEEE, 2006:594-601. [5] RABAUD V, BELONGIE S. Counting crowded moving objects[C]//Proceedings of the 2006 IEEE Conference on Computer Vision and Pattern Recognition. Piscataway, NJ:IEEE, 2006:705-711. [6] 韩迎辉,伏林.基于鱼眼视频图像的人群人数估计算法的研究[J].电子器件,2014,37(6):1111-1115.(HAN Y H, FU L. Research on estimation algorithm of crowd counting based on fisheye video image[J]. Chinese Journal of Electron Devices, 2014, 37(6):1111-1115.) [7] ALBIOL A, SILLA M J, ALBIOL A, et al. Video analysis using corner motion statistics[C]//Proceedings of the 2009 IEEE International Workshop on Performance Evaluation of Trackingand Surveillance. Piscataway, NJ:IEEE, 2009:31-38. [8] 曹志通,李晓华,周激流.改进的基于角点检测的视频人数统计方法[J].计算机应用,2017,37(S1):141-143,164.(CAO Z T, LI X H, ZHOU J L. Improved method for people counting in video sequences based on corner detection[J]. Journal of Computer Applications, 2017, 37(S1):141-143, 164.) [9] LEMPITSKY V S, ZISSERMAN A. Learning to count objects in images[C]//Proceedings of the 2010 International Conference on Neural Information Processing Systems. North Miami Beach, FL:Curran Associates Inc. 2010:1324-1332. [10] ARTETA C, LEMPITSKY V, NOBLE J A, et al. Interactive object counting[C]//Proceedings of the 2014 European Conference on Computer Vision. Berlin:Springer, 2014:504-518. [11] ZHANG Y Y, ZHOU D S, CHEN S Q, et al. Single-image crowd counting via multi-column convolutional neural network[C]//Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition. Piscataway, NJ:IEEE, 2016:589-597. [12] SAM D B, SURYA S, BABU R V. Switching convolutional neural network for crowd counting[C]//Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition. Piscataway, NJ:IEEE, 2017:4031-4039. [13] LOWE D G. Distinctive image features from scale-invariant keypoints[J]. International Journal of Computer Vision, 2004, 60(2):91-110. [14] CHEN K, GONG S G, XIANG T, et al. Cumulative attribute space for age and crowd density estimation[C]//Proceedings of the 2013 IEEE Conference on Computer Vision and Pattern Recognition. Piscataway, NJ:IEEE, 2013:2467-2474. [15] LOY C C, GONG S G, XIANG T. From semi-supervised to transfer counting of crowds[C]//Proceedings of the 2013 IEEE International Conference on Computer Vision. Piscataway, NJ:IEEE, 2013:2256-2263. [16] LOY C C, CHEN K, GONG S G, et al. Crowd counting and profiling:methodology and evaluation[M]//ALI S, NISHINO K, MANOCHA D, et al. Modeling, Simulation and Visual Analysis of Crowds. Berlin:Springer, 2013:347-382. [17] CHEN K, LOY C C, GONG S G, et al. Feature mining for localised crowd counting[C]//Proceedings of the 2012 British Machine Vision Conference. Durham, UK:BMVA, 2012:1-11. [18] University of Reading. PETS 2009 benchmark data[EB/OL].[2018-03-26]. http://www.cvg.reading.ac.uk/PETS2009/data.html. |