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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2507.03237 |
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| _version_ | 1866915371684986880 |
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| author | Raviv, Daniel Yepes, Juan D. Martinson, Eiki M. |
| author_facet | Raviv, Daniel Yepes, Juan D. Martinson, Eiki M. |
| contents | We demonstrate that, under orthographic projection and with a camera fixated on a point located on a rigid body, the rotation of that body can be analytically obtained by tracking only one other feature in the image. With some exceptions, any tracked point, regardless of its location on the body, yields the same value of the instantaneous rotation rate.
The proposed method is independent of the shape of the 3D object and does not require a priori knowledge about the scene. This algorithm is suited for parallel processing and can achieve segmentation of the scene by distinguishing points that do not belong to the same rigid body, simply because they do not produce the same value of the rotation. This paper presents an analytical derivation, simulation results, and results from real video data. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_03237 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A Vision-Based Closed-Form Solution for Measuring the Rotation Rate of an Object by Tracking One Point Raviv, Daniel Yepes, Juan D. Martinson, Eiki M. Computer Vision and Pattern Recognition We demonstrate that, under orthographic projection and with a camera fixated on a point located on a rigid body, the rotation of that body can be analytically obtained by tracking only one other feature in the image. With some exceptions, any tracked point, regardless of its location on the body, yields the same value of the instantaneous rotation rate. The proposed method is independent of the shape of the 3D object and does not require a priori knowledge about the scene. This algorithm is suited for parallel processing and can achieve segmentation of the scene by distinguishing points that do not belong to the same rigid body, simply because they do not produce the same value of the rotation. This paper presents an analytical derivation, simulation results, and results from real video data. |
| title | A Vision-Based Closed-Form Solution for Measuring the Rotation Rate of an Object by Tracking One Point |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2507.03237 |