【摘要】 近年来,低功耗全身动作捕捉在计算机视觉与自动化等领域都获得了广泛的关注。单目深度视觉与基于惯性的动作捕捉系统以其相对低廉的价格、良好的捕捉效果成为中小型用户的首选。然而,这两种系统却具有包括身体遮挡与误差漂移等一系列固有缺陷。因此创新性地提出一种基于RGB-D摄像机与惯性测量单元(IMU)数据融合的动作捕捉系统。该系统引入快速遮挡检测、动态阈值判断与权值分配策略,集成惯性测量技术和光学捕捉技术的优点,成本低、不易受环境影响。实验表明基于本方法的动作捕捉系统在精度、可靠性与稳定性上都具有良好的表现。更多还原

【Abstract】 Recently, low cost full Body Motion Tracking attracted tremendous attentions in the fields of Computer Vision and Automation. Single depth camera-and inertial-based motion tracking systems rapidly have become two primary options for small-business and individual consuming markets, due to their relatively inexpensive price and comparable performance. However, both depth camera-and inertial-based motion tracking systems have inherent disadvantages which cannot be eliminated theoretically and experimentally. For example, depth camera tracking mostly failed in the presence of occlusion while inertial sensor tracking usually suffered from drift errors. Therefore, a novel multiple-sensor fusion approach which seamlessly combined the data measured from a RGB-D Camera and several inertial measurement units(IMU) sensors was presented. The method had the characteristic of low cost and was less likely to be influenced by the environment by introducing several new algorithms, e.g., fast occlusion detection, dynamic threshold determination, and weighted value assignment. Experimental studies show that the method shows superior performance in terms of accuracy, reliability, and robustness.更多还原