Yu Pengfei, Yang Shourui, Chen Shengyong
Appl Opt. 2020 Dec 10;59(35):11104-11111. doi: 10.1364/AO.405703.
Time-of-flight (ToF) cameras can acquire the distance between the sensor and objects with high frame rates, offering bright prospects for ToF cameras in many applications. Low-resolution and depth errors limit the accuracy of ToF cameras, however. In this paper, we present a flexible accuracy improvement method for depth compensation and feature points position correction of ToF cameras. First, a distance-error model of each pixel in the depth image is established to model sinusoidal waves of ToF cameras and compensate for the measured depth data. Second, a more accurate feature point position is estimated with the aid of a high-resolution camera. Experiments evaluate the proposed method, and the result shows the root mean square error is reduced from 4.38 mm to 3.57 mm.
飞行时间(ToF)相机能够以高帧率获取传感器与物体之间的距离,这为ToF相机在许多应用中提供了广阔前景。然而,低分辨率和深度误差限制了ToF相机的精度。在本文中,我们提出了一种灵活的精度提升方法,用于ToF相机的深度补偿和特征点位置校正。首先,建立深度图像中每个像素的距离误差模型,以对ToF相机的正弦波进行建模并补偿测量的深度数据。其次,借助高分辨率相机估计更精确的特征点位置。实验对所提出的方法进行了评估,结果表明均方根误差从4.38毫米降至3.57毫米。