使用鱼眼相机进行道路线检测和三维重建

R. Boutteau, X. Savatier, Fabien Bonardi, J. Ertaud
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引用次数: 9

摘要

在未来的高级驾驶辅助系统(ADAS)中,对车辆环境的智能监控是一个关键问题。鱼眼相机已经变得流行,因为它们提供了一个全景与几个低成本的传感器。然而,目前的ADAS系统的应用有限,因为大多数底层图像处理都是为透视视图设计的。在这篇文章中,我们说明了过去十年来在全向视觉方面所做的理论工作如何有助于解决这一问题。为此,我们在实际条件下评估了一种基于统一球体模型的简单道路线检测算法。我们首先强调了在车辆中使用鱼眼相机的兴趣,然后我们概述了我们的方法,我们展示了我们在一组180图像上检测线条的实验结果,最后,我们展示了如何通过三角测量恢复线条的3D位置。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Road-line detection and 3D reconstruction using fisheye cameras
In future Advanced Driver Assistance Systems (ADAS), smart monitoring of the vehicle environment is a key issue. Fisheye cameras have become popular as they provide a panoramic view with a few low-cost sensors. However, current ADAS systems have limited use as most of the underlying image processing has been designed for perspective views only. In this article we illustrate how the theoretical work done in omnidirectional vision over the past ten years can help to tackle this issue. To do so, we have evaluated a simple algorithm for road line detection based on the unified sphere model in real conditions. We firstly highlight the interest of using fisheye cameras in a vehicle, then we outline our method, we present our experimental results on the detection of lines on a set of 180 images, and finally, we show how the 3D position of the lines can be recovered by triangulation.
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