Local probability based safe region detection for autonomous driving

P. Jeong, S. Nedvschi, M. Daniliuc
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引用次数: 1

Abstract

This paper proposes a new approach to detect the driving region and to detect the driving possible region from image sequence. To achieve this, we use local adaptive threshold and local probability for detecting the driving region and for detecting the driving possible region, respectively. Here are the three main aspects. The first one is the driving region detection. For this we use the local adaptive threshold. The second one is to recognize the driving possible region. To do this, we use a randomly selected initial seed and its extension using the distance between local probabilities. The third one is to combine the driving and the driving possible regions. It gives better results for safe autonomous driving. Sometimes, the driving region is not detected correctly due to very great noise factors. In this case the possible driving region still helps autonomous driving.
基于局部概率的自动驾驶安全区域检测
本文提出了一种新的检测驱动区域的方法,并从图像序列中检测出可能的驱动区域。为了实现这一点,我们分别使用局部自适应阈值和局部概率来检测驱动区域和检测驱动可能区域。以下是三个主要方面。首先是驱动区域检测。为此,我们使用局部自适应阈值。二是识别驱动可能区域。为此,我们使用随机选择的初始种子及其使用局部概率之间的距离进行扩展。三是将驱动区域与驱动可能区域结合起来。它为安全的自动驾驶提供了更好的结果。有时,由于噪声因素非常大,无法正确检测驱动区域。在这种情况下,可能的驾驶区域仍然有助于自动驾驶。
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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