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用于城市规模三维重建的摄像头与激光传感器融合技术

Sensor fusion of cameras and a laser for city-scale 3D reconstruction.

作者信息

Bok Yunsu, Choi Dong-Geol, Kweon In So

机构信息

Robotics and Computer Vision Lab., KAIST, 291 Daehak-ro, Yuseong-gu, Daejeon 305-701, Korea.

出版信息

Sensors (Basel). 2014 Nov 4;14(11):20882-909. doi: 10.3390/s141120882.

Abstract

This paper presents a sensor fusion system of cameras and a 2D laser sensorfor large-scale 3D reconstruction. The proposed system is designed to capture data on afast-moving ground vehicle. The system consists of six cameras and one 2D laser sensor,and they are synchronized by a hardware trigger. Reconstruction of 3D structures is doneby estimating frame-by-frame motion and accumulating vertical laser scans, as in previousworks. However, our approach does not assume near 2D motion, but estimates free motion(including absolute scale) in 3D space using both laser data and image features. In orderto avoid the degeneration associated with typical three-point algorithms, we present a newalgorithm that selects 3D points from two frames captured by multiple cameras. The problemof error accumulation is solved by loop closing, not by GPS. The experimental resultsshow that the estimated path is successfully overlaid on the satellite images, such that thereconstruction result is very accurate.

摘要

本文提出了一种用于大规模三维重建的相机与二维激光传感器的传感器融合系统。所提出的系统旨在采集快速行驶的地面车辆的数据。该系统由六个相机和一个二维激光传感器组成,它们通过硬件触发实现同步。与之前的工作一样,三维结构的重建是通过逐帧估计运动并累积垂直激光扫描来完成的。然而,我们的方法并不假设接近二维运动,而是利用激光数据和图像特征在三维空间中估计自由运动(包括绝对尺度)。为了避免与典型三点算法相关的退化问题,我们提出了一种新算法,该算法从多个相机捕获的两帧中选择三维点。误差累积问题通过闭环解决,而不是通过全球定位系统(GPS)。实验结果表明,估计路径成功叠加在卫星图像上,从而重建结果非常准确。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6b72/4279516/ea2fde21ead3/sensors-14-20882f2.jpg

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