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| Format: | Preprint |
| Veröffentlicht: |
2023
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| Online-Zugang: | https://arxiv.org/abs/2312.14697 |
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| _version_ | 1866917557680734208 |
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| author | Rodriguez, Joaquin Lew-Yan-Voon, Lew-Fock-Chong Martins, Renato Morel, Olivier |
| author_facet | Rodriguez, Joaquin Lew-Yan-Voon, Lew-Fock-Chong Martins, Renato Morel, Olivier |
| contents | Polarization information of the light can provide rich cues for computer vision and scene understanding tasks, such as the type of material, pose, and shape of the objects. With the advent of new and cheap polarimetric sensors, this imaging modality is becoming accessible to a wider public for solving problems such as pose estimation, 3D reconstruction, underwater navigation, and depth estimation. However, we observe several limitations regarding the usage of this sensorial modality, as well as a lack of standards and publicly available tools to analyze polarization images. Furthermore, although polarization camera manufacturers usually provide acquisition tools to interface with their cameras, they rarely include processing algorithms that make use of the polarization information. In this paper, we review recent advances in applications that involve polarization imaging, including a comprehensive survey of recent advances on polarization for vision and robotics perception tasks. We also introduce a complete software toolkit that provides common standards to communicate with and process information from most of the existing micro-grid polarization cameras on the market. The toolkit also implements several image processing algorithms for this modality, and it is publicly available on GitHub: https://github.com/vibot-lab/Pola4all_JEI_2023. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2312_14697 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Pola4All: survey of polarimetric applications and an open-source toolkit to analyze polarization Rodriguez, Joaquin Lew-Yan-Voon, Lew-Fock-Chong Martins, Renato Morel, Olivier Computer Vision and Pattern Recognition Polarization information of the light can provide rich cues for computer vision and scene understanding tasks, such as the type of material, pose, and shape of the objects. With the advent of new and cheap polarimetric sensors, this imaging modality is becoming accessible to a wider public for solving problems such as pose estimation, 3D reconstruction, underwater navigation, and depth estimation. However, we observe several limitations regarding the usage of this sensorial modality, as well as a lack of standards and publicly available tools to analyze polarization images. Furthermore, although polarization camera manufacturers usually provide acquisition tools to interface with their cameras, they rarely include processing algorithms that make use of the polarization information. In this paper, we review recent advances in applications that involve polarization imaging, including a comprehensive survey of recent advances on polarization for vision and robotics perception tasks. We also introduce a complete software toolkit that provides common standards to communicate with and process information from most of the existing micro-grid polarization cameras on the market. The toolkit also implements several image processing algorithms for this modality, and it is publicly available on GitHub: https://github.com/vibot-lab/Pola4all_JEI_2023. |
| title | Pola4All: survey of polarimetric applications and an open-source toolkit to analyze polarization |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2312.14697 |