Free-space detection with fish-eye cameras

Simon Hanisch, Rubén Heras Evangelio, H. Tadjine, Michael Pätzold
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引用次数: 7

Abstract

Advance Driver Assistance Systems (ADAS) have gained huge attention in the last decades. One of the fundamental steps of the video processing chain is the detection of areas where the car can drive through, i.e. free-space. In this paper we present an approach for the detection of free-space which is based on image segmentation and classification of the obtained image segments. For the image segmentation step we use several state-of-the-art approaches. The classification is done by a random-forest classifier trained to label the image segments with one of three geometric classes (ground, sky, vertical) based on spatial, color and shape features. Segments labelled as ground are used to detect the free-space area in front of the car. Furthermore, a comparison of the results obtained by using different segmentation approaches is provided.
用鱼眼相机进行自由空间探测
在过去的几十年里,高级驾驶辅助系统(ADAS)获得了巨大的关注。视频处理链的基本步骤之一是检测汽车可以行驶的区域,即自由空间。本文提出了一种基于图像分割和图像分段分类的自由空间检测方法。对于图像分割步骤,我们使用了几种最先进的方法。分类是由随机森林分类器完成的,该分类器根据空间、颜色和形状特征,用三种几何类别(地面、天空、垂直)中的一种来标记图像片段。标记为地面的部分用于检测汽车前方的自由空间区域。最后,对不同分割方法的分割结果进行了比较。
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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