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王文中, 王兆其, 邓小明, 夏时洪, 邱显杰. 基于局部先验模型的单目视频人体运动跟踪[J]. 计算机辅助设计与图形学学报, 2011, 23(9): 1545-1552.
引用本文: 王文中, 王兆其, 邓小明, 夏时洪, 邱显杰. 基于局部先验模型的单目视频人体运动跟踪[J]. 计算机辅助设计与图形学学报, 2011, 23(9): 1545-1552.
Wang Wenzhong, Wang Zhaoqi, Deng Xiaoming, Xia Shihong, Qiu Xianjie. Monocular Tracking of Human Motion with Local Prior Models[J]. Journal of Computer-Aided Design & Computer Graphics, 2011, 23(9): 1545-1552.
Citation: Wang Wenzhong, Wang Zhaoqi, Deng Xiaoming, Xia Shihong, Qiu Xianjie. Monocular Tracking of Human Motion with Local Prior Models[J]. Journal of Computer-Aided Design & Computer Graphics, 2011, 23(9): 1545-1552.

基于局部先验模型的单目视频人体运动跟踪

Monocular Tracking of Human Motion with Local Prior Models

  • 摘要: 在基于模型的单目视频人体运动跟踪中,视频图像信息往往不足以恢复人体姿态,通常需要加入对姿态的先验约束才能得到合理的解.为了有效地刻画人体运动过程的时变动态特征,提出局部先验模型,其中包括局部动态过程和局部姿态分布密度,通过在样本空间中检索出相似姿态的集合,并利用该集合学习模型参数来比较精确地刻画人体的运动规律.实验结果表明,与全局动态模型相比,局部先验模型有效地克服了肢体自遮挡和肢体混淆等问题,取得了更好的跟踪结果.

     

    Abstract: A novel approach to modelling the dynamics of human motion is presented.The proposed method utilizes locally learnt prior models to encode the time-varying characteristics of human motion.The local priors consist of the probability density of poses and dynamical process of motions.For each input image,the proposed method automatically learns the parameters of these models from a set of training examples that closely match with the query.The experimental results showed that the proposed method outperforms those with global motion models.

     

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