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| Main Authors: | , , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2410.21308 |
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| _version_ | 1866916457241116672 |
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| author | Zhang, Wanyu Zhang, Jiaqi Ge, Dongdong Lin, Yu Yang, Huiwen Liu, Huikang Ye, Yinyu |
| author_facet | Zhang, Wanyu Zhang, Jiaqi Ge, Dongdong Lin, Yu Yang, Huiwen Liu, Huikang Ye, Yinyu |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_21308 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | A Robust Anchor-based Method for Multi-Camera Pedestrian Localization Zhang, Wanyu Zhang, Jiaqi Ge, Dongdong Lin, Yu Yang, Huiwen Liu, Huikang Ye, Yinyu Computer Vision and Pattern Recognition Image and Video Processing 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. |
| title | A Robust Anchor-based Method for Multi-Camera Pedestrian Localization |
| topic | Computer Vision and Pattern Recognition Image and Video Processing |
| url | https://arxiv.org/abs/2410.21308 |