The developing time-of-flight (TOF) camera is an attractive device for the robot vision system to capture real-time three-dimensional (3D) images, but the sensor suffers from the limit of low resolution and precision of images. This article proposes an approach to automatic generation of an imaging model in the 3D space for error correction. Through observation data, an initial coarse model of the depth image can be obtained for each TOF camera. Then, its accuracy is improved by an optimization method. Experiments are carried out using three TOF cameras. Results show that the accuracy is dramatically improved by the spatial correction model.

中文翻译：

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多视图飞行时间视觉传感器深度图像的误差校正

正在开发的飞行时间 (TOF) 相机是机器人视觉系统捕获实时 3D (3D) 图像的一种有吸引力的设备，但传感器受到图像分辨率和精度低的限制。本文提出了一种在 3D 空间中自动生成成像模型以进行纠错的方法。通过观察数据，可以获得每个TOF相机的深度图像的初始粗略模型。然后，通过优化方法提高其精度。使用三个 TOF 相机进行实验。结果表明，空间校正模型显着提高了精度。