Camera Motion Estimation from RGB-D-Inertial Scene Flow
Fuente:
arXiv
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| Auteurs principaux: | , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866929327997714432 |
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| author | Cerezo, Samuel Civera, Javier |
| author_facet | Cerezo, Samuel Civera, Javier |
| contents | In this paper, we introduce a novel formulation for camera motion estimation that integrates RGB-D images and inertial data through scene flow. Our goal is to accurately estimate the camera motion in a rigid 3D environment, along with the state of the inertial measurement unit (IMU). Our proposed method offers the flexibility to operate as a multi-frame optimization or to marginalize older data, thus effectively utilizing past measurements. To assess the performance of our method, we conducted evaluations using both synthetic data from the ICL-NUIM dataset and real data sequences from the OpenLORIS-Scene dataset. Our results show that the fusion of these two sensors enhances the accuracy of camera motion estimation when compared to using only visual data. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_17251 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Camera Motion Estimation from RGB-D-Inertial Scene Flow Cerezo, Samuel Civera, Javier Computer Vision and Pattern Recognition In this paper, we introduce a novel formulation for camera motion estimation that integrates RGB-D images and inertial data through scene flow. Our goal is to accurately estimate the camera motion in a rigid 3D environment, along with the state of the inertial measurement unit (IMU). Our proposed method offers the flexibility to operate as a multi-frame optimization or to marginalize older data, thus effectively utilizing past measurements. To assess the performance of our method, we conducted evaluations using both synthetic data from the ICL-NUIM dataset and real data sequences from the OpenLORIS-Scene dataset. Our results show that the fusion of these two sensors enhances the accuracy of camera motion estimation when compared to using only visual data. |
| title | Camera Motion Estimation from RGB-D-Inertial Scene Flow |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2404.17251 |