论文标题
道路障碍位置和动态特征提取，结合对象检测，立体差距和光流数据
Road obstacles positional and dynamic features extraction combining object detection, stereo disparity maps and optical flow data
论文作者
论文摘要
智能车辆导航系统中最相关的任务之一是检测障碍物。重要的是，出于导航目的的视觉感知系统要确定障碍，并且重要的是，该系统可以提取可能影响车辆行为的基本信息，无论是为人类驾驶员发出警报还是指导自动驾驶汽车，以便能够做出驾驶决策。在本文中，我们提出了一种识别从这些物体中使用的障碍，位置，深度和运动信息的障碍和提取的方法，这些方法采用了仅从被动视力中获得的数据。我们对两个不同的数据集进行了实验，并且获得的结果表明，使用深度和运动模式来评估障碍的潜在威胁状态，这表明了良好的功效。
One of the most relevant tasks in an intelligent vehicle navigation system is the detection of obstacles. It is important that a visual perception system for navigation purposes identifies obstacles, and it is also important that this system can extract essential information that may influence the vehicle's behavior, whether it will be generating an alert for a human driver or guide an autonomous vehicle in order to be able to make its driving decisions. In this paper we present an approach for the identification of obstacles and extraction of class, position, depth and motion information from these objects that employs data gained exclusively from passive vision. We performed our experiments on two different data-sets and the results obtained shown a good efficacy from the use of depth and motion patterns to assess the obstacles' potential threat status.
