Hands and Arms Motion Estimation of a Car Driver with Depth Image Sensor by Using Particle Filter
Hands and Arms Motion Estimation of a Car Driver with Depth Image Sensor by Using Particle Filter
复制标题
使用粒子滤波器对具有深度图像传感器的汽车驾驶员的手和手臂运动进行估计
DOI：
10.1007/978-3-319-05533-6_8
复制
发表时间：
2014
期刊：
影响因子：
--
通讯作者：
N. Ikoma
中科院分区：
文献类型：
--
作者：
N. Ikoma
已经提出了通过利用深度图像传感器（具体地，Microsoft Xbox 360的KINECT）来估计汽车驾驶中的手和手臂运动。与传统的使用普通视觉传感器的研究相比，深度传感器为场景中的手和手臂提供了丰富的信息。特别是，由深度传感器检测到的手臂区域已被用来估计手和手臂的运动比传统的研究更准确。随着手部和手臂区域提取精度的提高，本文提出在粒子滤波框架中加入一些有意切换手部左右的粒子。这个想法减少了左和右的错误（相反）决定，它将增加从相反决定中自动恢复的机会。在驾驶模拟器环境下录制的视频的视觉和深度的实验表明，该方法的有效性。
Estimation of hands and arms motion in a car driving by utilizing a depth image sensor, specifically, KINECT of Microsoft Xbox 360, has been proposed. Compared with conventional researches using ordinary vision sensor, depth sensor provides rich information for the hands and arms in the scene. Especially, arms’ regions detected by the depth sensor have been utilized to estimate the hands and arms motion more accurately than the conventional researches. As well as the increasing accuracy of the hands and arms region extraction, this paper proposes to incorporate some particles intentionally switching the left and the right of the hands in a framework of particle filter. This idea reduce the mistaken (opposite) determination of left and right and it will increase the opportunity to recover automatically from the opposite determination. Experiments over the recorded videos of vision and depth under a driving simulator environment show the efficiency of the proposed method.