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Sensor Fusion of Cameras and a Laser for City-Scale 3D Reconstruction

机译:相机和激光的传感器融合,用于城市规模的3D重建

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摘要

This paper presents a sensor fusion system of cameras and a 2D laser sensor for large-scale 3D reconstruction. The proposed system is designed to capture data on a fast-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 done by estimating frame-by-frame motion and accumulating vertical laser scans, as in previous works. 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 order to avoid the degeneration associated with typical three-point algorithms, we present a new algorithm that selects 3D points from two frames captured by multiple cameras. The problem of error accumulation is solved by loop closing, not by GPS. The experimental results show that the estimated path is successfully overlaid on the satellite images, such that the reconstruction result is very accurate.
机译:本文提出了一种用于大型3D重建的相机和2D激光传感器的传感器融合系统。拟议中的系统旨在捕获快速移动的地面车辆上的数据。该系统由六个摄像头和一个2D激光传感器组成,它们通过硬件触发器同步。如先前的工作一样,通过估计逐帧运动并累积垂直激光扫描来完成3D结构的重建。但是,我们的方法并不假设接近2D运动,而是使用激光数据和图像特征来估计3D空间中的自由运动(包括绝对比例)。为了避免与典型的三点算法相关的退化,我们提出了一种新算法,该算法从多个摄像机捕获的两个帧中选择3D点。误差累积的问题是通过闭环而不是通过GPS解决的。实验结果表明,所估计的路径成功地覆盖在卫星图像上,重建结果非常准确。

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