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单目视觉下目标三维行为的时间尺度不变建模及识别

王蒙 戴亚平 王庆林

王蒙, 戴亚平, 王庆林. 单目视觉下目标三维行为的时间尺度不变建模及识别. 自动化学报, 2014, 40(8): 1644-1653. doi: 10.3724/SP.J.1004.2014.01644
引用本文: 王蒙, 戴亚平, 王庆林. 单目视觉下目标三维行为的时间尺度不变建模及识别. 自动化学报, 2014, 40(8): 1644-1653. doi: 10.3724/SP.J.1004.2014.01644
WANG Meng, DAI Ya-Ping, WANG Qing-Lin. Time-scale Invariant Modeling and Classifying for Object Behaviors in 3D Space Based on Monocular Vision. ACTA AUTOMATICA SINICA, 2014, 40(8): 1644-1653. doi: 10.3724/SP.J.1004.2014.01644
Citation: WANG Meng, DAI Ya-Ping, WANG Qing-Lin. Time-scale Invariant Modeling and Classifying for Object Behaviors in 3D Space Based on Monocular Vision. ACTA AUTOMATICA SINICA, 2014, 40(8): 1644-1653. doi: 10.3724/SP.J.1004.2014.01644

单目视觉下目标三维行为的时间尺度不变建模及识别

doi: 10.3724/SP.J.1004.2014.01644
基金项目: 

本文责任编委周杰

详细信息
    作者简介:

    戴亚平 北京理工大学自动化学院教授.主要研究方向为机动目标跟踪,基于网络的远程控制,多传感器数据融合.E-mail:daiyaping.bit@gmail.com

    通讯作者:

    王蒙 北京理工大学自动化学院博士研究生. 主要研究方向为计算机视觉,模式识别及信息融合.Email:vicong68@gmail.com

Time-scale Invariant Modeling and Classifying for Object Behaviors in 3D Space Based on Monocular Vision

  • 摘要: 提出一种单目视觉下在线识别目标三维行为的方法. 该方法用匹配的标记点估计帧间相似变换,然后转换相似矩阵到对数空间以获取一致的四自由度运动参数序列. 为解决持续时间敏感问题,提出基于多边形近似算法的时间尺度不变特征,并用动态规划实现特征序列的在线提取. 在行为识别阶段,基于动态时间规整训练有限类别行为模板用于匹配测试行为序列. 实验结果表明,该行为模板较对比方法类别可分性平均提高60%以上,并且可用于在线识别连续视频中的未知行为.
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出版历程
  • 收稿日期:  2013-07-18
  • 修回日期:  2013-12-16
  • 刊出日期:  2014-08-20

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