School of Integrated Technology, Gwangju Institute of Science and Technology, Gwangju 61005, Korea.
Sensors (Basel). 2022 Apr 20;22(9):3155. doi: 10.3390/s22093155.
Skeleton data, which is often used in the HCI field, is a data structure that can efficiently express human poses and gestures because it consists of 3D positions of joints. The advancement of RGB-D sensors, such as Kinect sensors, enabled the easy capture of skeleton data from depth or RGB images. However, when tracking a target with a single sensor, there is an occlusion problem causing the quality of invisible joints to be randomly degraded. As a result, multiple sensors should be used to reliably track a target in all directions over a wide range. In this paper, we proposed a new method for combining multiple inaccurate skeleton data sets obtained from multiple sensors that capture a target from different angles into a single accurate skeleton data. The proposed algorithm uses density-based spatial clustering of applications with noise (DBSCAN) to prevent noise-added inaccurate joint candidates from participating in the merging process. After merging with the inlier candidates, we used Kalman filter to denoise the tremble error of the joint's movement. We evaluated the proposed algorithm's performance using the best view as the ground truth. In addition, the results of different sizes for the DBSCAN searching area were analyzed. By applying the proposed algorithm, the joint position accuracy of the merged skeleton improved as the number of sensors increased. Furthermore, highest performance was shown when the searching area of DBSCAN was 10 cm.
骨架数据在人机交互领域中经常被使用，因为它由关节的 3D 位置组成，所以是一种能够高效表达人体姿势和动作的数据结构。Kinect 传感器等 RGB-D 传感器的进步使得从深度或 RGB 图像中轻松捕获骨架数据成为可能。然而，当使用单个传感器跟踪目标时，会出现遮挡问题，导致不可见关节的质量随机降级。因此，应该使用多个传感器在广泛的范围内可靠地跟踪各个方向的目标。在本文中，我们提出了一种新的方法，用于将从不同角度捕获目标的多个传感器获得的多个不准确的骨架数据集组合成单个准确的骨架数据。所提出的算法使用基于密度的带有噪声的空间聚类应用程序（DBSCAN）来防止添加噪声的不准确关节候选参与合并过程。与内点候选合并后，我们使用卡尔曼滤波器去除关节运动的抖动误差。我们使用最佳视图作为地面实况来评估所提出算法的性能。此外，还分析了 DBSCAN 搜索区域的不同大小的结果。通过应用所提出的算法，随着传感器数量的增加，合并后的骨架的关节位置精度得到了提高。此外，当 DBSCAN 的搜索区域为 10cm 时，性能最高。
