There is a need for methods to recognize night pedestrian to reduce pedestrian traffic accidents at night. In this paper, we proposed the method that converts images using continuous nighttime images from in‐vehicle camera. The proposed method performs feature extraction that does not depend on one's own vehicle speed because inputting continuous nighttime images, and the function of convolution layer that performs dimensionality reduction. In order to confirm the effectiveness of the proposed method, we prepared the images of simulation and camera. The nighttime images were conversed with the proposed method. After conversion, we calculated the recognition performance by applying object detection which is an object recognition method. We showed the proposed method is more robust against the own vehicle speed change.

中文翻译：

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使用车载摄像头提高夜间图像的可视性，以供行人识别

需要一种识别夜间行人的方法以减少夜间的行人交通事故。在本文中，我们提出了一种使用车载摄像机连续夜间图像进行图像转换的方法。所提出的方法执行特征提取，该特征提取由于输入连续的夜间图像而不依赖于自己的车辆速度，并且执行卷积层的功能降低了维数。为了确认该方法的有效性，我们准备了仿真图像和摄像机图像。夜间图像与提出的方法进行了交谈。转换后，我们通过应用对象检测（一种对象识别方法）来计算识别性能。我们证明了所提出的方法对自己的车速变化更鲁棒。