用固定锚点提升多摄像头行人定位精度，抗相机参数误差。
A Robust Anchor-based Method for Multi-Camera Pedestrian Localization
- 引入固定位置锚点，降低相机参数偏差影响
- 实测在模拟与真实数据上定位误差显著下降
- 适合部署在相机校准不准的监控场景
本文针对基于视觉的行人定位问题，即利用图像和相机参数估计行人位置。实际中，标定的相机参数常偏离真实值，导致定位不准确。为此，我们提出一种基于锚点的方法，利用固定位置的锚点减少相机参数误差的影响。提供了理论分析，证明该方法具有鲁棒性。在模拟、真实世界及公开数据集上的实验表明，相比无锚点方法，本方法显著提升了定位精度，并对相机参数噪声保持稳健。
原文摘要 · Abstract (English)
This paper addresses the problem of vision-based pedestrian localization, which estimates a pedestrian's location using images and camera parameters. In practice, however, calibrated camera parameters often deviate from the ground truth, leading to inaccuracies in localization. To address this issue, we propose an anchor-based method that leverages fixed-position anchors to reduce the impact of camera parameter errors. We provide a theoretical analysis that demonstrates the robustness of our approach. Experiments conducted on simulated, real-world, and public datasets show that our method significantly improves localization accuracy and remains resilient to noise in camera parameters, compared to methods without anchors.
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