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Generator of road marking textures and associated ground truth Applied to the evaluation of road marking detection

机译:道路标记纹理和相关地面真相的生成器应用于道路标记检测的评估

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To increase driving safety, many researcher works on Advanced Driving Assistance Systems (ADAS) have been developed and embedded in real prototypes during the last decades. For some of these applications like Lane Keeping System, lane perception is an essential task. For others applications like Emergency Brake Assist, lane perception modules provide useful information helping the system to select only the most dangerous obstacles. Proposed solutions to perform lane detection become more and more elaborated, however no generic solution has been proposed to calculate performances of these algorithms. Lots of solutions have been proposed to perform this lane detection. However, no generic solution has actually been proposed to quantify the quality of such applications. It is appearing that this evaluation task is now very important and critical. Most of the existing evaluation stages can be classified in two main parts. In the first case, evaluation is based on natural images databases with ground truth of road marking and/or geometrical truth of lanes. In the second case, evaluation uses virtual data and simulated images. The first one is relatively hard to perform because it is based on manual labeling of natural images. The second one has automatic labeling clustering but a realistic virtual environment is required and more precisely both realistic road bitumen and road marking textures. This paper presents an efficient solution in order to simulate roads environment for the evaluation stage of road marking detection algorithms. Moreover, a powerful tool dedicated to the road marking texture generation is proposed. It takes into account both imperfection and wear of the road marking. A virtual database using this tool will be applied on a set of road marking extractor to validate the evaluation process with our virtual approach.
机译:为了提高驾驶安全性,在过去的几十年中,已经开发了许多高级驾驶辅助系统(ADAS)的研究人员并将其嵌入到真实的原型中。对于诸如车道保持系统之类的一些应用,车道感知是一项必不可少的任务。对于紧急制动辅助等其他应用,车道感知模块提供有用的信息,可帮助系统仅选择最危险的障碍物。提出的用于执行车道检测的解决方案变得越来越复杂,但是尚未提出用于计算这些算法性能的通用解决方案。已经提出了许多解决方案来执行该车道检测。但是,实际上没有提出通用解决方案来量化此类应用程序的质量。看来,这一评估任务现在非常重要和关键。现有的大多数评估阶段可以分为两个主要部分。在第一种情况下,评估基于具有道路标记的地面真实性和/或车道的几何真实性的自然图像数据库。在第二种情况下,评估使用虚拟数据和模拟图像。第一个相对难以执行,因为它基于自然图像的手动标记。第二个具有自动标签聚类功能,但需要一个逼真的虚拟环境,更确切地说,既要具有逼真的道路沥青,又要具有道路标记纹理。本文针对道路标志检测算法的评估阶段,提出了一种有效的模拟道路环境的解决方案。此外,提出了专用于道路标记纹理生成的强大工具。它同时考虑了道路标记的不完善性和磨损。使用此工具的虚拟数据库将应用于一组道路标记提取器,以使用我们的虚拟方法验证评估过程。

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