期刊文献+

分块跟踪中的目标模板更新方法 被引量:15

Target template update method in fragment tracking
原文传递
导出
摘要 在基于模式匹配的目标跟踪算法中,由于受遮挡、自身外观变化的影响,模板更新问题一直是目标跟踪的一个难题,因为遮挡和外观变化均表现为目标内灰度的变化,但由障碍物遮挡引起的灰度变化不能更新为模板;而由目标自身引起的灰度变化又要即时地更新为模板。为此,提出一种带有遮挡和外观变化判断的局部模板更新算法。算法使用分块模板并根据目标中变化的信息分别来自目标和背景的概率来区别外观变化和遮挡这两种情况。目标被部分遮挡时,通过不更新模板来防止障碍物信息混入模板;目标外观变化时,提出一种新的局部模板更新算法以适应目标的不断变化。实验结果表明,该算法既能较好地适应目标的外观变化,又具有较强的抗遮挡能力,比整体模板更新算法具有更好的鲁棒性。 Influenced by appearance changes and occlusions, template updating has been one of the most difficult problems in the object tracking algorithms based on pattern matching. Because both appearance changes and occlusions can lead to the changes in the intensity of object, however, changes that result from the obstacles can' t be updated as the template; while changes that result from the object in itself should be updated in time. Therefore, a local template update method with the discrimination between occlusions and appearance changes is presented in this paper, The proposed method uses the fragment template for the tracking and distinguishes occlusions from appearance changes according to the probabilities of which varied gray level information belongs to the target and to the background region. The template is preserved to prevent the information of the obstacles from contaminating the template when the target has been partially occluded; while a new adaptive local template update algorithm is used in the ease of appearance changes. Experimental results are presented to demonstrate that our algorithm can be adaptive to the appearance changes as well as occlusions and is more robust than the total model update strategy.
出处 《中国图象图形学报》 CSCD 北大核心 2011年第6期976-982,共7页 Journal of Image and Graphics
关键词 分块跟踪 模板更新 外观变化 遮挡 fragment tracking template update appearance change occlusion
作者简介 齐美彬(1969-),男,教授。2007年于合肥工业大学获信息处理专业博士学位,主要研究方向为数字图像处理、DSP技术及应用。E-mail:qimeibin@163.com。
  • 相关文献

参考文献9

  • 1Porikli F, Tuzel O, Meet P. Covariance tracking using model update based on lie algebra[ C]//Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition. New York, NY, USA: IEEE Associate Press, 2006:728-735.
  • 2Nummiaro K, Koller-Meier E, Gool L Van. An adaptive color-based particle filter [ J ]. Image and Vision Computing, 2003, 21(1) :99-110.
  • 3Collins R T, Liu Y X, Leordeanu M. Online selection of discriminative tracking features [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2005, 27 (10): 1631-1643.
  • 4沈志熙,杨欣,黄席樾.均值漂移算法中的目标模型更新方法研究[J].自动化学报,2009,35(5):478-483. 被引量:35
  • 5Babua R V, Perez P, Bouthemy P. Robust tracking with motion estimation and local kernel-based color modeling[J]. Image and Vision Computing, 2007, 25(8): 1205-1216.
  • 6Pan Jiyan, Hu Bo. Robust object tracking against template drift [ C ] //IEEE Conference on Image Processing. New York,USA : 1EEE Associate Press,2007,3 : 353-356.
  • 7Junseok Kwon, Kyoung Mu Lee. Tracking of a non-rigid object via patch-based dynamic appearance modeling and adaptive basin hopping monte carlo sampling [ C ]//2009 IEEE Conference on Computer Vision and Pattern Recognition. New York, USA:IEEE Associate Press, 2009 : 1208-1215.
  • 8Adam A, Rivlin E, Shimshoni I. Robust fragments-based tracking using the integral histogram [ C ]//Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. New York, NY, USA : IEEE Associate Press, 2006 : 798-805.
  • 9周妍,胡波,张建秋.基于粒子滤波器和风险决策跟踪遮挡目标的方法[J].电子学报,2007,35(2):350-353. 被引量:12

二级参考文献22

  • 1Weng S K.Kuo C M,Tu S K.Video object tracking using adaptive Kalmall filter.dournal of visual Communication and Image Representation,2006,17(6):1190-1208
  • 2Chen Y Q,Rui Y,Huang T S.Multicue HMM.UKF for real-time contour tracking.IEEE Transactions on Pattern Analysis and Machine Intelligence,2006,28(9):1525-1529
  • 3Nummiaro K.Meier E K.Gool L J V.An adaptive colorbased particle filter.Image and Vision Computing,2003.21(1):99-110
  • 4Nummiaro K,Meier E K,Cool L J V.Object tracking with an adaptive color-based particle filter.In:Proceedings of the 24th DAGM Symposium on Pattern Recognition.London,UK:Springer.2002.353-360
  • 5Comaniciu D,Ramesh V.Mead:l skift and optimal prediction for efficient obiect tracking.In:Proceedings of IEEE International Conference on Image Processing.Vancouver,Canada:IEEE,2000.70-73
  • 6Comaniciu D.Meer P.Mean shift:a robust approach toward feature space analysis.IEEE Transactions on Pattern Analysis and Machine Intelligence,2002,24(5):603-619
  • 7Comaniciu D,Ramesh V,Meer P.Kernel-based object tracking.IEEE Transactions on Pattern Analysis and Machine Intelligence,2003,25(5):564-577
  • 8Porikl F.Tuzel O.Meer P.Covariance tracking using model update based on Lie algebra.In:Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.New York,USA:IEEE,2006.728-735
  • 9Collins R T,Liu Y X.Leordeanu M.Online selection of discriminative tracking features.IEEE Transactions on Pattern Analysis and Machine Intellgence,2005,27(10):1631-1643
  • 10Nguyen H T,Worring M,van den Boomgaard R.Ocelusion robust adaptive template tracking.In:Proceedings of the 8th International Conference 0n Computer Vision.Vancouver,Canada:IEEE,2001.678-683

共引文献44

同被引文献149

引证文献15

二级引证文献81

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部