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An image processing system for driver assistance

机译:用于驾驶员辅助的图像处理系统

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摘要

System for automated image analysis are useful for a variety of tasks. Their importance is still growing due to technological advances and increased social acceptance. Especially driver assistance systems have reached a high level of sophistication. Fully or partly autonomously guided vehicles, particularly for road traffic, require highly reliable algorithms due to the conditions imposed by natural environments. At the Institut fur Neuroinformatik, methods for analyzing driving relevant scenes by computer vision are developed in cooperation with several partners from the automobile industry. We present a system extracting important information from an image taken by a CCD camera installed at the rear-view mirror in a car. The approach is divided into a sequential and a parallel phase of sensor and information processing. Three main tasks, namely initial segmentation (object detection), object tracking and object classification are realized by integration in the sequential phase and by fusion in the parallel phase. The main advantage of this approach is integrative coupling of different algorithms providing partly redundant information.
机译:用于自动图像分析的系统可用于多种任务。由于技术进步和社会接受度的提高,它们的重要性仍在增长。尤其是驾驶员辅助系统已经达到很高的水平。由于自然环境的强加条件,完全或部分自主驾驶的车辆,特别是用于道路交通的车辆,需要高度可靠的算法。在神经信息学研究所,与汽车行业的一些合作伙伴合作,开发了通过计算机视觉分析驾驶相关场景的方法。我们提出了一种系统,该系统从安装在汽车后视镜中的CCD摄像机拍摄的图像中提取重要信息。该方法分为传感器和信息处理的顺序和并行阶段。通过顺序阶段的集成和并行阶段的融合来实现初始分割(对象检测),对象跟踪和对象分类这三个主要任务。这种方法的主要优点是提供部分冗余信息的不同算法的集成耦合。

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