Are Euler angles a useful rotation parameterisation for pose estimation with Normalizing Flows?
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866918184778465280 |
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| author | Sfikas, Giorgos Nikolaidou, Konstantina Papadopoulou, Foteini Retsinas, George Kesidis, Anastasios L. |
| author_facet | Sfikas, Giorgos Nikolaidou, Konstantina Papadopoulou, Foteini Retsinas, George Kesidis, Anastasios L. |
| contents | Object pose estimation is a task that is of central importance in 3D Computer Vision. Given a target image and a canonical pose, a single point estimate may very often be sufficient; however, a probabilistic pose output is related to a number of benefits when pose is not unambiguous due to sensor and projection constraints or inherent object symmetries. With this paper, we explore the usefulness of using the well-known Euler angles parameterisation as a basis for a Normalizing Flows model for pose estimation. Isomorphic to spatial rotation, 3D pose has been parameterized in a number of ways, either in or out of the context of parameter estimation. We explore the idea that Euler angles, despite their shortcomings, may lead to useful models in a number of aspects, compared to a model built on a more complex parameterisation. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_02277 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Are Euler angles a useful rotation parameterisation for pose estimation with Normalizing Flows? Sfikas, Giorgos Nikolaidou, Konstantina Papadopoulou, Foteini Retsinas, George Kesidis, Anastasios L. Computer Vision and Pattern Recognition Object pose estimation is a task that is of central importance in 3D Computer Vision. Given a target image and a canonical pose, a single point estimate may very often be sufficient; however, a probabilistic pose output is related to a number of benefits when pose is not unambiguous due to sensor and projection constraints or inherent object symmetries. With this paper, we explore the usefulness of using the well-known Euler angles parameterisation as a basis for a Normalizing Flows model for pose estimation. Isomorphic to spatial rotation, 3D pose has been parameterized in a number of ways, either in or out of the context of parameter estimation. We explore the idea that Euler angles, despite their shortcomings, may lead to useful models in a number of aspects, compared to a model built on a more complex parameterisation. |
| title | Are Euler angles a useful rotation parameterisation for pose estimation with Normalizing Flows? |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2511.02277 |