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Pedestrian detection by video processing in automotive night vision system

机译:汽车夜视系统中视频处理的行人检测

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The paper takes the automatic detection of pedestrians from a vehicle into consideration using an automotive night vision system. Accidents involving pedestrians at night cause a significant part of deaths in the roads. Therefore, the authors present a design of the automotive night vision system that combines the passive solutions, i.e. those using thermal vision, and active, which use the near infrared camera. Passive system provides greater range of detection, while the active one works in a closer range and offers more natural images. Beside the design of hardware also a software part for the automatic detection of pedestrians was prepared and tested. The software for object detection and classification uses modern digital signal processing algorithms like: connected component labeling (CCL), histogram of oriented gradients (HOG), and support vector machine (SVM). Tests performed on real night vision recordings show a very high efficiency of the proposed solution thus confirm correctness of the design. Furthermore, the presented night vision system for automatic detection of pedestrians can be implemented in vehicles at an acceptable, i.e., quite moderate cost.
机译:本文考虑了使用汽车夜视系统对车辆行人的自动检测。夜间涉及行人的事故在道路上造成很大一部分死亡。因此,作者提出了一种汽车夜视系统的设计,该系统结合了无源解决方案,即使用热视觉的解决方案和使用近红外摄像机的有源解决方案。被动系统可提供更大的检测范围,而主动系统可在更近的范围内工作并提供更自然的图像。除了硬件设计之外,还准备并测试了用于自动检测行人的软件部分。用于对象检测和分类的软件使用现代数字信号处理算法,例如:连接组件标记(CCL),定向梯度直方图(HOG)和支持向量机(SVM)。在真实夜视记录上进行的测试表明,所提出解决方案的效率非常高,因此可以确认设计的正确性。此外,所提出的用于自动检测行人的夜视系统可以以可接受的,即相当适中的成本在车辆中实施。

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