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第5期 修春波,等:模糊直方图模型的运动目标跟踪 ·945· 移,从而影响跟踪性能的问题,提出了基于模糊 YU Lei,XIA Yeru,YANG Liangjie.A target tracking al- 直方图模型的目标跟踪方法,采用模糊划分色度 gorithm for the improved understanding,diagnosing and 等级的方式建立目标直方图模型,弱化了色度划 tracking system[J].Applied science and technology,2018, 分阈值对直方图模型的影响,降低了目标模型对 45(4):76-81. 光照变化等干扰的敏感性,提高了跟踪方法的适 [8]YIN Minghao,ZHANG Jin,SUN Hongguang,et al.Multi- 应性。跟踪实验结果表明,在光照变化明显等情 cue-based CamShift guided particle filter tracking[J].Ex- 况下,与传统跟踪方法相比,该方法具有更好的 pert systems with applications,2011,38(5):6313-6318. 跟踪性能,能够完成在不同光照条件下的目标跟 [9]HUANG Danchi,LI Lijuan.Face tracking algorithm based 踪,且目标定位与跟踪所需计算量较小,运算时 on improved Camshift and surf algorithm[J].Journal of 间满足实时性的要求。 computational information systems,2015,11(3):893-901. [10]HSIA C H.LIOU Y J.CHIANG J S.Directional predic- 参考文献: tion camshift algorithm based on adaptive search pattern [I]QU Shiru,LIU Ningning.Face detection and tracking for moving object tracking[J].Journal of real-time image method based on SMQT and CAMSHIFTIJ].Journal of processing,2016,12(1):183-195. computational information systems,2015,11(14): [1l]修春波,卢少磊,任晓.基于微分信息融合的Mean 5153-5162 Shit改进跟踪算法[).系统工程与电子技术,2014, [2]黄晋英,宋国浩,兰艳亭,等.交比不变的Camshift跟踪 36(5):10041009. 方法).光学精密工程,2016,24(4:945-953 XIU Chunbo,LU Shaolei,REN Xiao.Improved mean HUANG Jinying,SONG Guohao,LAN Yanting,et al. shift tracking algorithm based on differential Camshift tracking based on constant cross ratio[J].Optics information[J].Systems engineering and electronics, and precision engineering,2016,24(4):945-953 2014,36(5):1004-1009 [3]刘威,陈先桥,初秀民.基于置信规则推理方法的雷达目 [12]修春波,魏世安,万蓉凤.二维联合特征模型的自适应 标跟踪J.哈尔滨工程大学学报,2016,37(6):826-831 均值漂移目标跟踪[J].光电子·激光,2015,26(2): 342-351. LIU Wei,CHEN Xianqiao,CHU Xiumin.Radar target XIU Chunbo,WEI Shian,WAN Rongfeng.CamShift tar- tracking via belief rule-based methodology[J].Journal of get tracking based on two-dimensional joint characterist- Harbin Engineering University,2016,37(6):826-831. ics[J].Journal of optoelectronicslaser,2015,26(2): 「4]王春平,王暐,刘江义,等.基于色度饱和度-角度梯度直 342-351. 方图特征的尺度自适应核相关滤波跟踪凹.光学精密工 [13]张天翼,杨忠,韩家明,等.基于连续自适应均值漂移和 程,2016,249:2293-2301. 立体视觉的无人机目标跟踪方法.应用科技,2018, WANG Chunping,WANG Wei,LIU Jiangyi,et al.Scale 45(2):55-59 adaptive kernelized correlation filter tracking based on ZHANG Tianyi,YANG Zhong,HAN Jiaming,et al.Ap- HHS-OG feature[J].Optics and precision engineering, proach of vision navigation of UAV based on continu- 2016,24(9):2293-2301 ously adaptive mean-shift and stereo vision[J].Applied [5]朱齐丹,韩瑜,蔡成涛.全景视觉非线性核相关滤波目标 science and technology,2018,45(2):55-59. 跟踪技术[J].哈尔滨工程大学学报,2018,39(7): [14]刘明华,汪传生,王宪伦.基于多特征自适应融合的均 1220-1226 值迁移目标跟踪算法[J】.光电子·激光,2015,26(8): ZHU Qidan.HAN Yu,CAI Chengtao.Omni-directional 1583-1592 visual object tracking using nonlinear kernelized correla- LIU Minghua,WANG Chuansheng,WANG Xianlun. tion filters[J].Journal of Harbin Engineering University, Mean-shift target tracking algorithm based on adaptive 2018,397):1220-1226 multi-features fusion[J].Journal of optoelectronics laser. [6]LIU Shenshen,ZHOU Pu,MA Chanyu.Athlete tracking 2015,26(8):1583-1592 model based on morphological noise removal camshift al- [15]夏瑜,吴小俊,李菊,等.基于多特征自适应融合的分类 gorithm[J].International journal of earth science and en- 采样跟踪算法).光电子激光,2016,27(3)325-331. gineering,2015,8(5):2246-2251 XIA Yu,WU Xiaojun,LI Ju,et al.Classified sampling [7]于蕾,夏业儒,杨良洁.改进理解诊断跟踪系统的目标跟 tracking algorithm based on adaptive multiple features fu- 踪方法U.应用科技,2018.45(4):76-81 sion[J].Journal of optoelectronics.laser,2016,27(3)移,从而影响跟踪性能的问题,提出了基于模糊 直方图模型的目标跟踪方法,采用模糊划分色度 等级的方式建立目标直方图模型,弱化了色度划 分阈值对直方图模型的影响,降低了目标模型对 光照变化等干扰的敏感性,提高了跟踪方法的适 应性。跟踪实验结果表明,在光照变化明显等情 况下,与传统跟踪方法相比,该方法具有更好的 跟踪性能,能够完成在不同光照条件下的目标跟 踪,且目标定位与跟踪所需计算量较小,运算时 间满足实时性的要求。 参考文献: QU Shiru, LIU Ningning. Face detection and tracking method based on SMQT and CAMSHIFT[J]. Journal of computational information systems, 2015, 11(14): 5153–5162. [1] 黄晋英, 宋国浩, 兰艳亭, 等. 交比不变的 Camshift 跟踪 方法 [J]. 光学精密工程, 2016, 24(4): 945–953. HUANG Jinying, SONG Guohao, LAN Yanting, et al. Camshift tracking based on constant cross ratio[J]. Optics and precision engineering, 2016, 24(4): 945–953. [2] 刘威, 陈先桥, 初秀民. 基于置信规则推理方法的雷达目 标跟踪 [J]. 哈尔滨工程大学学报, 2016, 37(6): 826–831. LIU Wei, CHEN Xianqiao, CHU Xiumin. Radar target tracking via belief rule-based methodology[J]. Journal of Harbin Engineering University, 2016, 37(6): 826–831. [3] 王春平, 王暐, 刘江义, 等. 基于色度饱和度−角度梯度直 方图特征的尺度自适应核相关滤波跟踪 [J]. 光学精密工 程, 2016, 24(9): 2293–2301. WANG Chunping, WANG Wei, LIU Jiangyi, et al. Scale adaptive kernelized correlation filter tracking based on HHS-OG feature[J]. Optics and precision engineering, 2016, 24(9): 2293–2301. [4] 朱齐丹, 韩瑜, 蔡成涛. 全景视觉非线性核相关滤波目标 跟踪技术 [J]. 哈尔滨工程大学学报, 2018, 39(7): 1220–1226. ZHU Qidan, HAN Yu, CAI Chengtao. Omni-directional visual object tracking using nonlinear kernelized correla￾tion filters[J]. Journal of Harbin Engineering University, 2018, 39(7): 1220–1226. [5] LIU Shenshen, ZHOU Pu, MA Chanyu. Athlete tracking model based on morphological noise removal camshift al￾gorithm[J]. International journal of earth science and en￾gineering, 2015, 8(5): 2246–2251. [6] 于蕾, 夏业儒, 杨良洁. 改进理解诊断跟踪系统的目标跟 踪方法 [J]. 应用科技, 2018, 45(4): 76–81. [7] YU Lei, XIA Yeru, YANG Liangjie. A target tracking al￾gorithm for the improved understanding, diagnosing and tracking system[J]. Applied science and technology, 2018, 45(4): 76–81. YIN Minghao, ZHANG Jin, SUN Hongguang, et al. Multi￾cue-based CamShift guided particle filter tracking[J]. Ex￾pert systems with applications, 2011, 38(5): 6313–6318. [8] HUANG Danchi, LI Lijuan. Face tracking algorithm based on improved Camshift and surf algorithm[J]. Journal of computational information systems, 2015, 11(3): 893–901. [9] HSIA C H, LIOU Y J, CHIANG J S. Directional predic￾tion camshift algorithm based on adaptive search pattern for moving object tracking[J]. Journal of real-time image processing, 2016, 12(1): 183–195. [10] 修春波, 卢少磊, 任晓. 基于微分信息融合的 Mean Shift 改进跟踪算法 [J]. 系统工程与电子技术, 2014, 36(5): 1004–1009. XIU Chunbo, LU Shaolei, REN Xiao. Improved mean shift tracking algorithm based on differential information[J]. Systems engineering and electronics, 2014, 36(5): 1004–1009. [11] 修春波, 魏世安, 万蓉凤. 二维联合特征模型的自适应 均值漂移目标跟踪 [J]. 光电子·激光, 2015, 26(2): 342–351. XIU Chunbo, WEI Shian, WAN Rongfeng. CamShift tar￾get tracking based on two-dimensional joint characterist￾ics[J]. Journal of optoelectronics·laser, 2015, 26(2): 342–351. [12] 张天翼, 杨忠, 韩家明, 等. 基于连续自适应均值漂移和 立体视觉的无人机目标跟踪方法 [J]. 应用科技, 2018, 45(2): 55–59. ZHANG Tianyi, YANG Zhong, HAN Jiaming, et al. Ap￾proach of vision navigation of UAV based on continu￾ously adaptive mean-shift and stereo vision[J]. Applied science and technology, 2018, 45(2): 55–59. [13] 刘明华, 汪传生, 王宪伦. 基于多特征自适应融合的均 值迁移目标跟踪算法 [J]. 光电子·激光, 2015, 26(8): 1583–1592. LIU Minghua, WANG Chuansheng, WANG Xianlun. Mean-shift target tracking algorithm based on adaptive multi-features fusion[J]. Journal of optoelectronics·laser, 2015, 26(8): 1583–1592. [14] 夏瑜, 吴小俊, 李菊, 等. 基于多特征自适应融合的分类 采样跟踪算法 [J]. 光电子·激光, 2016, 27(3): 325–331. XIA Yu, WU Xiaojun, LI Ju, et al. Classified sampling tracking algorithm based on adaptive multiple features fu￾sion[J]. Journal of optoelectronics·laser, 2016, 27(3): [15] 第 5 期 修春波,等:模糊直方图模型的运动目标跟踪 ·945·
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