汪济洲,鲁昌华,蒋薇薇.一种基于随机场多运动目标跟踪算法[J].电子测量与仪器学报,2017,31(6):909-913
一种基于随机场多运动目标跟踪算法
New multi target tracking algorithm based on conditional random field
  
DOI:10.13382/j.jemi.2017.06.013
中文关键词:  多目标跟踪  条件随机场  跟踪子对
英文关键词:multi target tracking  conditional random field  pair of tracklets
基金项目:大学生创客实验室建设计划(2015ckjh068)、基于QoS的4G LTE系统切换策略的研究(KJ2015B1105908)资助项目
作者单位
汪济洲 1. 合肥工业大学计算机与信息学院合肥230031; 2.合肥学院合肥230061 
鲁昌华 合肥工业大学计算机与信息学院合肥230031 
蒋薇薇 合肥工业大学计算机与信息学院合肥230031 
AuthorInstitution
Wang Jizhou 1. School of Computer and Information, Hefei University of Technology, Hefei 230031,China; 2. Hefei University,Hefei 230061,China 
Lu Changhua School of Computer and Information, Hefei University of Technology, Hefei 230031,China 
Jiang Weiwei School of Computer and Information, Hefei University of Technology, Hefei 230031,China 
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中文摘要:
      多运动目标跟踪是智能视频监控系统的重要内容。由于目标数量众多且目标之间相互遮挡,会造成跟踪轨迹不连续,这是多目标跟踪问题的难点,也是当前流行算法无法解决的研究的问题。利用目标对相互之间的位置信息受到外界干扰较少的特点,提出基于条件随机场多目标跟踪。与以前针对所有目标的外形特征不同,算法对跟踪子对进行标示。采用分层结构,由低阶状态作为输入序列到高阶,通过代价函数最小化,从而得到最终连续跟踪轨迹。能有效解决复杂环境下多目标不连续的问题。算法对于外形类似的被跟踪目标以及相互遮挡严重的情况有比较明显的优势,与当前优秀的算法相比,实验表明本文算法在定量分析和定性分析上均有较好的结果。
英文摘要:
      Multi target tracking is very important in intelligent video surveillance system. Occlusions among many moving objects and objects with similar appearance that could result in incontinuous trajectory are challenging problems in this field. Based on the fact that the relative positions remain stable between two close pairs, a novel multi target tracking algorithm based on conditional random field is presented in this paper. Unlike previous approaches which focus only on appearance and motion models for all targets, we consider discriminative features for distinguishing difficult pairs of targets with sets of labels. Multi level is adopted by this means, in which the set of tracklets produced by previous level is used as an input. And tracking problem is transformed into an energy minimization problem including a set of unary function for a continuous trajectory and a set of pairwise function for pairs of tracklets. This new method is more powerful in deal with objects with similar appearance and badly occlusions compared to state of art methods. Qualitative and quantitative experimental results show that this new method has a better performance.
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