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基于隨機投影和稀疏表示的跟蹤算法

郁道銀,  王悅行,  陳曉冬,  汪毅

郁道銀, 王悅行, 陳曉冬, 汪毅. 基于隨機投影和稀疏表示的跟蹤算法[J]. 電子與信息學(xué)報, 2016, 38(7): 1602-1608. doi: 10.11999/JEIT151064
引用本文: 郁道銀, 王悅行, 陳曉冬, 汪毅. 基于隨機投影和稀疏表示的跟蹤算法[J]. 電子與信息學(xué)報, 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 & 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 & Information Technology, 2016, 38(7): 1602-1608. doi: 10.11999/JEIT151064

基于隨機投影和稀疏表示的跟蹤算法

doi: 10.11999/JEIT151064

Visual Tracking Based on Random Projection and Sparse Representation

  • 摘要: 針對目標(biāo)跟蹤過程中存在的諸多技術(shù)問題，該文提出一種魯棒的目標(biāo)跟蹤方法。首先，該文采用基于稀疏表示的全局模板描述目標(biāo)的表觀狀態(tài)，通過構(gòu)造正負(fù)模板以區(qū)分目標(biāo)和背景；然后采用隨機投影法對表示模板和候選目標(biāo)進行降維，以降低算法的時間復(fù)雜度；采用粒子濾波法作為目標(biāo)的運動模型，通過多項式重采樣方法進行粒子重采樣，以保持粒子的多樣性；設(shè)計了正負(fù)模板更新策略，將正模板分為固定集和更新集，對這兩部分在相似度計算和正模板更新時采取不同的處理方法，并且在其中加入目標(biāo)遮擋的判決機制，從而可以有效避免遮擋的影響；實驗結(jié)果表明，該算法能夠準(zhǔn)確跟蹤受遮擋、運動模糊等多種復(fù)雜場景的目標(biāo)，與現(xiàn)有跟蹤方法相比，所提算法具有更好的準(zhǔn)確性和穩(wěn)定性。
    Abstract: A robust object tracking method is proposed to deal with technical issues during tracking. Firstly, the global template based on sparse representation is used to describe object appearance, while positive and negative modules are built to separate the object from the background. Then, Random Projection (RP) is used to reduce the dimension of modules and candidate objects, which could release the calculation burden. Furthermore, the Particle Filter (PF) is used as the object motion model, and the multi-normal resample method is used to maintain the diversity of particles. To alleviate module drift problem, the positive module is divided into static module and changeable module, while different modules are dealt with different ways, and sparse reconstruction error is used to determine whether the object is occluded. Experiment results on numerous challenging videos show that the proposed method has better performance in accuracy and stability in comparison with state-of-the-art tracking methods.
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出版歷程
  • 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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