Efficient 3D voxel reconstruction of human shape within robotic work cells
Efficient 3D voxel reconstruction of human shape within robotic work cells
复制标题
在机器人工作单元内高效重建人体形状的 3D 体素
DOI：
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发表时间：
2012
期刊：
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通讯作者：
B. Vogel‐Heuser
中科院分区：
文献类型：
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作者：
D. Stengel;T. Wiedemann;B. Vogel‐Heuser
本文提出了一种基于轮廓形状的机器人工作单元体素重建方法。提出了一种从机器人运动学到重构步骤的遮挡过程，即依赖于时间的占用空间。轴值与来自机器人的表面模型一起用于对来自移动设备的遮挡进行建模。展示了一种简化的就地帧校准的基于图像的方法，并与常规的基于标记的方法进行了比较。介绍了一种背景模型的学习方法，该方法包括重叠来自机器人的图像区域，并提供了更高的学习速度。出于效率的原因，实现是在GPU上完成的。显示并讨论了在工业环境中使用五个摄像头在质量和帧速率方面所取得的性能。
In this paper an efficient voxel reconstruction method within a robotic work cell by means of shape from silhouette is presented. A procedure is proposed which includes occlusions from the robot's kinematics into the reconstruction step, i.e. the time-dependent occupied space. Axis values together with surface models from the robot are used for modeling occlusions coming from the moving device. An image-based method for simplified in-place frame calibration is shown and compared to a regular marker-based method. A learning method for background models is introduced, which includes overlapping image areas from the robot and offers improved learning rates. For efficiency reasons the implementation was done on the GPU. The achieved performance using five cameras in an industrial setting is shown and discussed with respect to quality and frame-rates.