[1]夏瑜,吴小俊.基于新颖相似度的视觉跟踪算法[J].南京师范大学学报(工程技术版),2008,08(04):068-72.
 Xia Yu,Wu Xiaojun.Visual Tracking Algorithm Based on a Novel Similarity Function[J].Journal of Nanjing Normal University(Engineering and Technology),2008,08(04):068-72.
点击复制

基于新颖相似度的视觉跟踪算法
分享到:

南京师范大学学报(工程技术版)[ISSN:1006-6977/CN:61-1281/TN]

卷:
08卷
期数:
2008年04期
页码:
068-72
栏目:
出版日期:
2008-12-30

文章信息/Info

Title:
Visual Tracking Algorithm Based on a Novel Similarity Function
作者:
夏瑜;吴小俊;
江南大学信息工程学院, 江苏无锡214122
Author(s):
Xia YuWu Xiaojun
School of Information Engineering,Jiangnan University,Wuxi 214122,China
关键词:
粒子滤波 直方图 相似性度量 H SV Bhattacharyya系数
Keywords:
partic le filte r h istog ram sim ilar ity m easure H SV Bhattacharyya coe ffic ient
分类号:
TP391.41
摘要:
模板匹配是视觉跟踪领域中的重要环节.以粒子滤波为跟踪框架,提出了一种新颖的模板匹配的统计特征相似性指标,引进了加权因子有效抑制目标边界噪声干扰和匹配区域背景成分的影响,同时突出了目标特征的权重.由于完全不同模板图像统计特征也会存在交集,导致相似性偏差,所以融合基于HSV颜色空间的相似度能够修正偏差,改善匹配函数峰值特性,使得搜索目标得到全局最优解,最终实现鲁棒跟踪.实验结果表明,模板匹配具有良好的峰值特性,算法在跟踪目标存在变形、噪声、遮挡时也可以达到比较理想的跟踪效果.
Abstract:
Temp la tem atch ing is an im portant link of v isua l track ing. A nove l tem plate statistical featurem atching sim -i larity criter ion is proposed w ith a track ing fram ework using particle filter. W e ighted factor is introduced to effec tive ly reduce the influence o f border no ise and background feature, and a great em inence is g iven to the im portance o f targe t feature. S im ilarity b ias m ay be got in the two com plete ly different temp la tes because of the intersection of statistica l features. The proposed m ethod can correct the bias and improv e the peak moda lity ofm a tch ing function by fusing sim ila rity based on H SV co lor system, so it can obta in the g lobal optim al so lu tion and robust tracking. Exper im enta l results show tha t tem plate m atch ing has an exce llen t peak d istr ibution, and the proposed track ing a lgor ithm exh ib its good precision and robustness in the presence o f no ise, defo rma tion and occ lusion.

参考文献/References:

[ 1] 王亮, 胡卫明, 谭铁牛. 人运动的视觉分析综述[ J]. 计算机学报, 2002( 3): 225-237.
W ang Liang, H uW e im ing, Tan T ien iu. A survey o f v isual ana lysis of hum an mo tion [ J] . Ch inese Journa l o f Computers, 2002( 3): 225-237. ( in Ch inese)
[ 2] LeeK W, Ryu SW, Lee S J, et a.l M o tion based object tracking w ith m ob ile cam era[ J] . E lectron ics Lette rs, 1998, 34( 3):256-258.
[ 3] Yang C, Duraisw am i R, Dav is L. E fficient m ean-shift track ing v ia a new sim ilar ity m easure [ C] / / IEEE Compu ter So ciety
Con ference on ComputerV ision and Pattern Recogn ition. Los A lam ito s: IEEE, 2005, 1: 176-183.
[ 4] Barron J, Fleet D, Beauchem in S. Pe rfo rm ance of optica l flow techn iques [ J] . Internationa l Journal of Com puter V is ion,1994, 12( 1): 42-77.
[ 5] Com aniciu D, Ram esh V, M eer P. Kerne-l based ob ject track ing[ J] . IEEE T ransactions on Pattern Ana lysis andM achine Itelligence, 2003, 25( 5): 564-577.
[ 6] Cheung G, Baker S, Kanade T. Shape- from-silhouette o f ar ticu lated ob jects and its use for hum an body k inem atics estim ation
and m otion cap ture[ C ] / / Proceed ings of the IEEE Conference on Compu terV ision and Pa ttern Recogn ition. M ad ison: IEEE,2003, 6( 1) : 77-84.
[ 7] Nguy en H T, Sm eu lders A W M. Robust track ing us ing fo reground-backg round texture disc rim ination[ J]. In t J Comput Vision, 2006, 69( 3) : 277-293.
[ 8] Com anic iuk D, M ee r P. M ean sh ift: a robust approach tow ard feature space ana lysis[ J]. IEEE Trans Actions Pattern Anal
M ach Intel,l 2002, 24( 5): 603-619.
[ 9] Go rdon N, Salmond D. Nove l approach to non- linea r and non-Gauss ian Bayesian state estim a tion[ J]. Proceed ings of Institute Electric Eng ineer ing, 1993, 140( 2): 107-113.
[ 10] 章毓晋. 图像工程[M ]. 2版. 北京: 清华大学出版社, 2007: 168-171.
Zhang Yujin. Im ag e Eng ineer ing[M ]. 2nd ed. Be ijing: Ts inghua University Press, 2007: 168-171. ( in Chinese)

相似文献/References:

[1]郑爱彬,张明.基于相关聚合直方图的CBIR[J].南京师范大学学报(工程技术版),2005,05(04):057.
 ZHENG Aibin,ZHANG Ming.The Research of the Correlation and Polymerization Histogram in CBIR[J].Journal of Nanjing Normal University(Engineering and Technology),2005,05(04):057.
[2]卞 乐,李天峰,韦 怡,等.HLBP与颜色特征自适应融合的粒子滤波目标跟踪改进算法[J].南京师范大学学报(工程技术版),2018,18(01):056.[doi:10.3969/j.issn.1672-1292.2018.01.008]
 Bian Le,Li Tianfeng,Wei Yi,et al.Improved Particle Filtering Target Tracking Algorithm forHLBP and Color Feature Adaptive Fusion[J].Journal of Nanjing Normal University(Engineering and Technology),2018,18(04):056.[doi:10.3969/j.issn.1672-1292.2018.01.008]

备注/Memo

备注/Memo:
基金项目: 2006年教育部新世纪优秀人才计划项目( NCET- 06- 0487)、国家自然科学基金( 60472060、60572034 )和江苏省自然科学基金( BK2006081 )资助项目.
通讯联系人: 夏 瑜, 硕士研究生, 讲师, 研究方向: 计算机视觉和目标跟踪. E-m ail:x iayu@ changh su. n et
更新日期/Last Update: 2013-04-24