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On September 7, 2026, arXiv cs.CV published research findings on using standardized license plates for multi-channel single-eye ranging. The study proposed a calibrated method that enables accurate three-dimensional spatial measurements based on standard license plates. The core of this method involves introducing a verification mechanism with metrological accuracy, aimed at addressing the uncertainty in depth estimation in traditional single-eye vision systems. By combining multi-channel data with standardized license plate features, the system can accurately calculate the distance to targets without the need for an external reference frame.
本研究提出一种基于标准化车牌的单目测距方法，并在 51 个美国车管所的实测环境中进行了精确验证。该方法利用车牌轮廓、字符高度及安装孔间距构建三个距离通道，通过共识门控逆方差融合算法进行数据合并与校正。实验涵盖 1 至 12 米的距离范围、最大 30 度的视角及五种光照条件，成功解决了低对比度与杂乱背景下的车牌定位问题。最终测距误差为：轮廓通道绝对百分比误差 4.32%，融合结果均值误差 5.79%、中位数误差 2.17%，且无单通道失效模式；姿态恢复精度满足要求。该算法可作为低成本距离估计方案，为其他传感器提供紧急备份基础。