Geometry reconstruction of urban scenes by tracking vertical edges

Tomohiko Gotoh, Mineichi Kudo, J. Toyama, M. Shimbo
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引用次数: 6

Abstract

Obtaining 3D geometric and texture information of urban scenes has received a great deal of attention in many fields such as civil engineering, traffic systems, car navigation systems, entertainment etc. It is, however, difficult to obtain a 3D description of an outdoor static scene because a camera is easily influenced by the environment such as lighting and background. In addition, it is expensive to obtain the description, especially in data input by human hand. To resolve these problems, we need an efficient and automatic framework for 3D modeling of city scenes. We propose an efficient method with epipolar-plane image analysis to model a 3D city scene along a road from an image sequence recorded by a camera boarded on a vehicle. With the method presented, we detect vertical edges and track the edges in a spatiotemporal solid of images. The locus of the edges gives us the distances from the path of the camera to the objects including the edges, such as buildings as well as their heights. The side of an object will be estimated as a rectangle, of which both sides are two different estimated edges with the same height. Our method is able to obtain both the distance and the height of the objects simultaneously. Therefore, the constructed model is expected to be stable and precise.
基于垂直边缘跟踪的城市场景几何重建
获取城市场景的三维几何和纹理信息在土木工程、交通系统、汽车导航系统、娱乐等领域受到了广泛的关注。然而,由于相机容易受到光线和背景等环境的影响,因此很难获得室外静态场景的3D描述。此外,获取描述的成本很高,尤其是人工输入的数据。为了解决这些问题,我们需要一个高效、自动化的城市场景三维建模框架。我们提出了一种利用极平面图像分析的有效方法,从车载摄像机记录的图像序列中模拟沿道路的三维城市场景。利用所提出的方法,我们检测垂直边缘并跟踪图像时空实体中的边缘。边缘的轨迹给了我们从相机路径到包含边缘的物体的距离,比如建筑物及其高度。物体的边将被估计为一个矩形,其两边是两个不同的估计边,具有相同的高度。我们的方法能够同时获得物体的距离和高度。因此,期望所构建的模型是稳定和精确的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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