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基于随机投影和稀疏表示的跟踪算法

郁道银 王悦行 陈晓冬 汪毅

郁道银, 王悦行, 陈晓冬, 汪毅. 基于随机投影和稀疏表示的跟踪算法[J]. 电子与信息学报, 2016, 38(7): 1602-1608. doi: 10.11999/JEIT151064
引用本文: 郁道银, 王悦行, 陈晓冬, 汪毅. 基于随机投影和稀疏表示的跟踪算法[J]. 电子与信息学报, 2016, 38(7): 1602-1608. doi: 10.11999/JEIT151064
YU Daoyin, WANG Yuexing, CHEN Xiaodong, WANG Yi. Visual Tracking Based on Random Projection and Sparse Representation[J]. Journal of Electronics and Information Technology, 2016, 38(7): 1602-1608. doi: 10.11999/JEIT151064
Citation: YU Daoyin, WANG Yuexing, CHEN Xiaodong, WANG Yi. Visual Tracking Based on Random Projection and Sparse Representation[J]. Journal of Electronics and Information Technology, 2016, 38(7): 1602-1608. doi: 10.11999/JEIT151064

基于随机投影和稀疏表示的跟踪算法

doi: 10.11999/JEIT151064

Visual Tracking Based on Random Projection and Sparse Representation

  • 摘要: 针对目标跟踪过程中存在的诸多技术问题,该文提出一种鲁棒的目标跟踪方法。首先,该文采用基于稀疏表示的全局模板描述目标的表观状态,通过构造正负模板以区分目标和背景;然后采用随机投影法对表示模板和候选目标进行降维,以降低算法的时间复杂度;采用粒子滤波法作为目标的运动模型,通过多项式重采样方法进行粒子重采样,以保持粒子的多样性;设计了正负模板更新策略,将正模板分为固定集和更新集,对这两部分在相似度计算和正模板更新时采取不同的处理方法,并且在其中加入目标遮挡的判决机制,从而可以有效避免遮挡的影响;实验结果表明,该算法能够准确跟踪受遮挡、运动模糊等多种复杂场景的目标,与现有跟踪方法相比,所提算法具有更好的准确性和稳定性。
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出版历程
  • 收稿日期:  2015-09-21
  • 修回日期:  2016-04-01
  • 刊出日期:  2016-07-19

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