[2] Yilmaz A, Javed O, Shah M. Object tracking: A survey[J]. ACM Computing Surveys, 2006,38(4): Article No. 13.
[3] Cannons K. A Review of Visual Tracking[R]. York University, Technical Report CSE-2008-07, 2008.
[4] Yang Hanxuan, Shao Ling, Zheng Feng, et al. Recent advances and trends in visual tracking: A review[J]. Neurocomputing, 2011,74(18):3823-3831.
[5] 蔡荣太,吴元昊,王明佳,等. 视频目标跟踪算法综述[J]. 电视技术, 2010,34(12):135-138.
[6] Comaniciu D, Ramesh V, Meer P. Real-time tracking of non-rigid objects using mean shift[C]// Proceedings of the 2000 IEEE Conference on Computer Vision and Pattern Recognition. 2000,2:142-149.
[7] Fukunaga K, Hostetler L. The estimation of the gradient of a density function, with applications in pattern recognition[J]. IEEE Transactions on Information Theory, 1975,21(1):32-40.
[8] Cannons K, Wildes R. Spatiotemporal oriented energy features for visual tracking[C]// Proceedings of the 8th Asian Conference on Computer Vision. 2007:532-543.
[9] Fieguth P, Terzopoulos D. Color-based tracking of heads and other mobile objects at video frame rates[C]// Proceedings of the 1997 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 1997:21-27.
[10] Wren C R, Azarbayejani A, Darrell T, et al. Pfinder: Real-time tracking of the human body[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1997,19(7):780-785.
[11] 闫庆森. 基于压缩感知的视频跟踪算法研究[D]. 太原:太原科技大学, 2014.
[12] 芦丹,李临生,闫庆森,等. 一种基于局部表示的精确跟踪算法[J]. 太原科技大学学报, 2015,36(6):411-415.
[13] Lu Dan, Li Linsheng, Yan Qingsen. A survey: Target tracking algorithm based on sparse representation[C]// Proceedings of the 7th International Symposium on Computational Intelligence and Design (ISCID). 2014,2:195-199.
[14] 闫庆森,李临生,徐晓峰,等. 视频跟踪算法研究综述[J]. 计算机科学, 2013,40(z1):204-209.
[15] Lowe D G. Object recognition from local scale-invariant features[C]// Proceedings of the 7th IEEE International Conference on Computer Vision. 1999,2:1150-1157.
[16] Bay H, Tuytelaars T, van Gool L. SURF: Speeded up robust features[C]// Proceedings of the 9th European Conference on Computer Vision. 2006:404-417.
[17] Manjunath B S, Ma Weiying. Texture features for browsing and retrieval of image data[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1996,18(8):837-842.
[18] Ojala T, Pietikainen M, Maenpaa T. Multiresolution gray-scale and rotation invariant texture classification with local binary patterns[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2002,24(7):971-987.
[19] Arulampalam M S, Maskell S, Gordon N, et al. A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking[J]. IEEE Transactions on Signal Processing, 2002,50(2):174-188.
[20] Cheng Yizhong. Mean shift, mode seeking, and clustering[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1995,17(8):790-799.
[21] Comaniciu D, Ramesh V, Meer P. Kernel-based object tracking[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2003,25(5):564-575.
[22] Comaniciu D, Ramesh V, Meer P. The variable bandwidth mean shift and data-driven scale selection[C]// Proceedings of the 8th IEEE International Conference on Computer Vision. 2001,1:438-445.
[23] Yang Changjiang, Duraiswami R, Davis L. Similarity measure for nonparametric kernel density based object tracking[C]// Proceedings of the 18th Annual Conference on Neural Information Processing Systems. 2004.
[24] Leung A P, Gong Shaogang. Mean-shift tracking with random sampling[C]// Proceedings of the 2006 British Machine Vision Conference. 2006,2:729-738.
[25] Hager G D, Dewan M, Stewart C V. Multiple kernel tracking with SSD[C]// Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 2004,1:790-797.
[26] Collins R T. Mean-shift blob tracking through scale space[C]// Proceedings of the 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 2003,2:234-240.
[27] Jeyakar J, Babu R V, Ramakrishnan K R. Robust object tracking with background-weighted local kernels[J]. Computer Vision and Image Understanding, 2008,112(3):296-309.
[28] Li Xiaohe, Zhang Taiyi, Shen Xiaodong, et al. Object tracking using an adaptive Kalman filter combined with mean shift[J]. Optical Engineering, 2010,49(2):020503-1-020503-3.
[29] 田浩,巨永锋,王培. 改进的抗遮挡MeanShift目标跟踪算法[J]. 计算机工程与应用, 2016,52(6):197-203.
[30] 徐火希. 基于改进Mean Shift的运动目标跟踪算法[J]. 兵器装备工程学报, 2016,37(2):127-130.
[31] 刘晴,唐林波,赵保军,等. 基于自适应多特征融合的均值迁移红外目标跟踪[J]. 电子与信息学报, 2012,34(5):1137-1141.
[32] 杜凯,巨永锋,靳引利,等. 自适应分块颜色直方图的MeanShift跟踪算法[J]. 武汉理工大学学报, 2012,34(6):140-144.
[33] Li Shuxiao, Wu Ou, Zhu Chengfei, et al. Visual object tracking using spatial context information and global tracking skills[J]. Computer Vision and Image Understanding, 2014,125:1-15.
[34] 聂义,阳波,廖武. 一种改进的meanshift目标跟踪算法[J]. 电脑与信息技术, 2015,23(5):12-14.
[35] 张恒,李由,李立春,等. 基于显著性加权的Mean Shift跟踪方法[J]. 光学技术, 2008,34(3):404-407.
[36] Ning Jifeng, Zhang Lei, Zhang D, et al. Robust mean-shift tracking with corrected background-weighted histogram[J]. IET Computer Vision, 2012,6(1):62-69.
[37] 陈定坤,杨艳. 一种改进的Mean-shift运动目标跟踪算法[J]. 半导体光电, 2015,36(1):160-164.
[38] 李鹏飞. 基于Mean Shift的目标跟踪算法研究[D]. 西安:西安电子科技大学, 2009.
[39] Harris C, Stephens M. A combined corner and edge detector[C]// Proceedings of the 4th Alvey Vision Conference. 1988:147-151.
[40] 王晓卫,王旭东,贺明. 基于直方图比的背景加权的Mean Shift目标跟踪算法[J]. 强激光与粒子束, 2016,28(5):13-17.
[41] Shen Chunhua, Brooks M J, van den Hengel A. Fast global kernel density mode seeking: Applications to localization and tracking[J]. IEEE Transactions on Image Processing, 2007,16(5):1457-1469.
[42] 毛晓波,郝向东,梁静. 基于ELM与Mean Shift的抗遮挡目标跟踪算法[J]. 郑州大学学报(工学版), 2016,37(1):1-5.
[43] 彭宁嵩,杨杰,刘志,等. Mean-Shift跟踪算法中核函数窗宽的自动选取[J]. 软件学报, 2005,16(9):1542-1550.
[44] 王勇,谭毅华,田金文. 基于Mean shift的核窗宽自适应目标跟踪新算法[J]. 数据采集与处理, 2009,24(6):762-766.
[45] Liu Baiyang, Huang Junzhou, Yang Lin, et al. Robust tracking using local sparse appearance model and K-selection[C]// Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition. 2011:1313-1320.
[46] 匡金骏,柴毅,熊庆宇. 结合标准对冲与核函数稀疏分类的目标跟踪[J]. 光学精密工程, 2012,20(11):2540-2547. |