An Easy Method for Extrinsic Calibration of Camera and Time-of-Flight Sensor
Tianyou Zhang, Jing Liu, Dragos Axinte, Xin Dong
Abstract
A multi-zone (typically 8×8) time-of-flight (ToF) sensor offers a low-cost, low-power, and compact solution for range measurement, making it ideal for specialized robotic applications. However, its low resolution limits its usability. Pairing a ToF sensor with a camera enhances depth perception and can solve the unscaled metric problem in mono depth estimation. Advances in deep learning further enable high-quality depth map reconstruction from ToF-camera data, providing a cost-effective alternative. However, accurate ToF-camera calibration remains a challenge due to ToF sensor’s coarse depth output.This work presents a simple yet effective method for the extrinsic calibration of a ToF sensor with an RGB camera using only a chessboard and two whiteboards. A tailored two-plane fitting algorithm is proposed specifically for the ToF sensor. Moreover, our approach leverages parallel lines with vanishing points and geometric constraints from plane intersections. This eliminates the need for robotic arm movements or SLAM-based sensor pose reconstruction, significantly reducing complexity while maintaining high accuracy. Experimental results demonstrate that our method lowers the root mean square (RMS) depth difference from 96.59 mm to 67.89 mm, underscoring its effectiveness in practical applications. Code is publicly available in https://github.com/Tianyou-Nottingham/ToF-Camera-Calibration.
BibTeX
@inproceedings{iros2025_aneasymethodfore,
title = {An Easy Method for Extrinsic Calibration of Camera and Time-of-Flight Sensor},
author = {Tianyou Zhang and Jing Liu and Dragos Axinte and Xin Dong},
booktitle = {IROS 2025},
year = {2025}
}