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Context aided pedestrian detection for danger estimation based on laser scanner and computer vision

机译:基于上下文的行人检测,基于激光扫描仪和计算机视觉的危险估计

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摘要

Road safety applications demand the most reliable sensor systems. In recent years, the advances in information technologies have led to more complex road safety applications able to cope with a high variety of situations. These applications have strong sensing requirements that a single sensor, with the available technology, cannot attain. Recent researches in Intelligent Transport Systems (ITS) try to overcome the limitations of the sensors by combining them. But not only sensor information is crucial to give a good and robust representation of the road environment; context information has a key role for reliable safety applications to provide reliable detection and complete situation assessment. This paper presents a novel approach for pedestrian detection using sensor fusion of laser scanner and computer vision. The application also takes advantage of context information, providing danger estimation for the pedestrians detected. Closing the loop, the danger estimation is later used, together with context information, as feedback to enhance the pedestrian detection process.
机译:道路安全应用需要最可靠的传感器系统。近年来,信息技术的进步导致了能够应对多种情况的更复杂的道路安全应用。这些应用具有强大的感测要求,而采用现有技术则无法实现单个传感器。智能运输系统(ITS)的最新研究试图通过组合传感器来克服传感器的局限性。但是,不仅传感器信息对于提供良好,可靠的道路环境表示至关重要;上下文信息对于可靠的安全应用程序提供可靠的检测和完整的状况评估具有关键作用。本文提出了一种使用激光扫描仪和计算机视觉传感器融合的行人检测新方法。该应用程序还利用上下文信息,为检测到的行人提供危险估计。闭合环路,然后将危险估计与上下文信息一起用作反馈,以增强行人检测过程。

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