基于随机遮挡的车辆再识别方法

Fengjiao Gao, Yumo Zhang, Tongjun Liu, Changjiang Song
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引用次数: 0

摘要

在计算机视觉领域,车辆再识别研究是一个重要的方向。目前已有很多研究者对车辆再识别问题进行了研究。但它们大多关注整体图像,而忽略遮挡图像,这可能更实用,也更具挑战性。本文提出了一种解决遥感图像遮挡问题的再识别方法,提取图像随机矩形区域的像素点,并将其覆盖到图像的其他位置。通过模拟遮挡图像的实验,验证了该方法的可行性。在真实遮挡图像数据集上的实验表明,本文提出的随机遮挡方法在解决遮挡问题方面优于随机擦除方法,可以获得更好的再识别结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A vehicle re-identification method based on random occlusion
In the computer vision field, vehicle re-identification research is an important direction. There have been many researchers doing research on vehicle re-identification. But they mostly focus on the overall image and ignore occluded images, which may be more practical and challenging. This paper proposed a re-identification method to solve the occlusion in remote sensing image, which extracted the pixels in the random rectangular area of the image and covers them to other positions of the image. The feasibility of the proposed random occlusion method was proved by experiments on simulated occlusion images. And experiments on real occlusion image data sets showed that the proposed random occlusion method was better than the random erasure method in solving the occlusion problem, and can obtain better re-identification results.
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