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    吕治国, 李 焱, 徐 昕. 快速的三维人手运动跟踪方法研究[J]. 计算机研究与发展, 2012, 49(7): 1398-1407.
    引用本文: 吕治国, 李 焱, 徐 昕. 快速的三维人手运动跟踪方法研究[J]. 计算机研究与发展, 2012, 49(7): 1398-1407.
    Lü Zhiguo, Li Yan, Xu Xin. Research on Fast 3D Hand Motion Tracking System[J]. Journal of Computer Research and Development, 2012, 49(7): 1398-1407.
    Citation: Lü Zhiguo, Li Yan, Xu Xin. Research on Fast 3D Hand Motion Tracking System[J]. Journal of Computer Research and Development, 2012, 49(7): 1398-1407.

    快速的三维人手运动跟踪方法研究

    Research on Fast 3D Hand Motion Tracking System

    • 摘要: 三维人手运动跟踪是人机交互领域的一个重要研究方向.提出了一种新的基于模型的三维人手运动跟踪方法,该方法将层次优化嵌入到基于粒子滤波器的跟踪框架中,通过在隐状态空间中对粒子采样来提高粒子滤波器采样效率.首先,提出了采用低维隐状态来描述人手的配置状态,并根据人手的生理运动约束建立人手动态模型;其次,为提高粒子在隐状态空间的采样效率,提出了采用层次遗传优化来快速地在局部寻找好的粒子,并以此作为重要度采样函数修正粒子滤波的采样算法.实验结果表明,该方法可以在人手自遮挡存在时的复杂背景下快速地对人手运动进行跟踪.

       

      Abstract: 3D hand tracking is one of the major research topics in the field of human-computer interaction. We present a novel model-based hand tracking method in this paper, which embeds hierarchical optimization method into the particle-filter-based tracking frames to improve the efficiency of particles sampling from the hidden state space. Firstly, the low dimension hidden state space is introduced to approximately describe the hand configuration state in the original high dimension configuration space, and the dynamic hand model in the hidden state space is presented according to the physiological constraints of hand motion. Secondly, to obtain more efficient particles during tracking, hierarchical genetic optimization method is regarded as the importance sampling function to modify the sampling algorithm of particle-filter. Experiments demonstrate that our approach can have fast tracking performance even under the clutter background when hand part self-occlusion exists.

       

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