SimpleDepthPose: Fast and Reliable Human Pose Estimation with RGBD-Images
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arXiv
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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866917947587428352 |
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| author | Bermuth, Daniel Poeppel, Alexander Reif, Wolfgang |
| author_facet | Bermuth, Daniel Poeppel, Alexander Reif, Wolfgang |
| contents | In the rapidly advancing domain of computer vision, accurately estimating the poses of multiple individuals from various viewpoints remains a significant challenge, especially when reliability is a key requirement. This paper introduces a novel algorithm that excels in multi-view, multi-person pose estimation by incorporating depth information. An extensive evaluation demonstrates that the proposed algorithm not only generalizes well to unseen datasets, and shows a fast runtime performance, but also is adaptable to different keypoints. To support further research, all of the work is publicly accessible. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2501_18478 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | SimpleDepthPose: Fast and Reliable Human Pose Estimation with RGBD-Images Bermuth, Daniel Poeppel, Alexander Reif, Wolfgang Computer Vision and Pattern Recognition In the rapidly advancing domain of computer vision, accurately estimating the poses of multiple individuals from various viewpoints remains a significant challenge, especially when reliability is a key requirement. This paper introduces a novel algorithm that excels in multi-view, multi-person pose estimation by incorporating depth information. An extensive evaluation demonstrates that the proposed algorithm not only generalizes well to unseen datasets, and shows a fast runtime performance, but also is adaptable to different keypoints. To support further research, all of the work is publicly accessible. |
| title | SimpleDepthPose: Fast and Reliable Human Pose Estimation with RGBD-Images |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2501.18478 |