论文标题
考虑表面损坏的道路表面检测和差异化
Road surface detection and differentiation considering surface damages
论文作者
论文摘要
在视觉感知领域的车辆和机器人导航的严重损坏和未铺设的道路上仍然要克服的挑战是可靠的路径和障碍物检测的任务。绝大多数研究是来自发达国家的情况良好的情景道路。这些作品应对道路表面上几乎没有变化的情况，甚至更少的情况表现出表面损害。在本文中，我们提出了一种考虑表面类型的变化，识别铺砌和未铺设的表面的方法，并检测到可能与驾驶安全有关的其他道路表面上的损坏和其他信息。我们还通过图像细分提出了一个新的地面真理，该真相是在我们的方法中使用的，这使我们能够评估结果。我们的结果表明，即使使用使用低成本相机捕获的图像，也可以将被动视力用于这些目的。
A challenge still to be overcome in the field of visual perception for vehicle and robotic navigation on heavily damaged and unpaved roads is the task of reliable path and obstacle detection. The vast majority of the researches have as scenario roads in good condition, from developed countries. These works cope with few situations of variation on the road surface and even fewer situations presenting surface damages. In this paper we present an approach for road detection considering variation in surface types, identifying paved and unpaved surfaces and also detecting damage and other information on other road surface that may be relevant to driving safety. We also present a new Ground Truth with image segmentation, used in our approach and that allowed us to evaluate our results. Our results show that it is possible to use passive vision for these purposes, even using images captured with low cost cameras.
