首页> 外文会议>International Conference on Soft Computing and Intelligent Systems;SCIS;International Symposium on Advanced Intelligent Systems;ISIS >Real-time motion estimation of car driver's hands and arms' direction in vision under possible mutual occlusion by particle filter
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Real-time motion estimation of car driver's hands and arms' direction in vision under possible mutual occlusion by particle filter

机译:在可能相互遮挡的情况下,通过粒子滤波器实时估计驾驶员手和手臂的视觉方向运动

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Motion of car driver's hands and arms have been tracked in vision by an elaborated particle filter with scenes being to have possible mutual occlusion by arms. Grasping angular positions over car steering by the two hands of car driver and arm's direction from each hand are estimated in time by particle filter. The mutual occlusion may occur due to arm's position to hide the other hand/arm. The scene has been formulated in a state space model with state vector consisting of the grasping angular positions and arms' directions. Smooth motion of the state vector has been described in a system model of the state space model. Observation model evaluates likelihood of hypothesized rectangle regions of hands around the steering and arms with elimination of other hand from the captured image. Real-time implementation of the proposed method to PC with C language and OpenCV library has been conducted with tracking experiments for several scenes.
机译:精心设计的粒子过滤器已在视觉上跟踪了汽车驾驶员的手和手臂的运动,且场景可能会被手臂相互遮挡。通过粒子过滤器,可以及时地估计出汽车驾驶员的两只手在汽车转向上的角位置以及每只手的手臂方向。由于手臂的位置隐藏另一只手/手臂,可能会发生相互咬合。该场景已用状态空间模型表示,该状态空间模型包含由抓握角度位置和手臂方向组成的状态向量。在状态空间模型的系统模型中已经描述了状态向量的平滑运动。观察模型通过从捕获的图像中消除另一只手来评估假想的围绕转向和手臂的手的矩形区域的可能性。通过对多个场景的跟踪实验,对采用C语言和OpenCV库的PC机实时实现了所提出的方法。

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