Enabling Robust, Real-Time Verification of Vision-Based Navigation through View Synthesis
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arXiv
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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866918082768797696 |
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| author | Neuhalfen, Marius Grzymisch, Jonathan Sanchez-Gestido, Manuel |
| author_facet | Neuhalfen, Marius Grzymisch, Jonathan Sanchez-Gestido, Manuel |
| contents | This work introduces VISY-REVE: a novel pipeline to validate image processing algorithms for Vision-Based Navigation. Traditional validation methods such as synthetic rendering or robotic testbed acquisition suffer from difficult setup and slow runtime. Instead, we propose augmenting image datasets in real-time with synthesized views at novel poses. This approach creates continuous trajectories from sparse, pre-existing datasets in open or closed-loop. In addition, we introduce a new distance metric between camera poses, the Boresight Deviation Distance, which is better suited for view synthesis than existing metrics. Using it, a method for increasing the density of image datasets is developed. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_02993 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Enabling Robust, Real-Time Verification of Vision-Based Navigation through View Synthesis Neuhalfen, Marius Grzymisch, Jonathan Sanchez-Gestido, Manuel Computer Vision and Pattern Recognition Robotics Image and Video Processing I.4.9 This work introduces VISY-REVE: a novel pipeline to validate image processing algorithms for Vision-Based Navigation. Traditional validation methods such as synthetic rendering or robotic testbed acquisition suffer from difficult setup and slow runtime. Instead, we propose augmenting image datasets in real-time with synthesized views at novel poses. This approach creates continuous trajectories from sparse, pre-existing datasets in open or closed-loop. In addition, we introduce a new distance metric between camera poses, the Boresight Deviation Distance, which is better suited for view synthesis than existing metrics. Using it, a method for increasing the density of image datasets is developed. |
| title | Enabling Robust, Real-Time Verification of Vision-Based Navigation through View Synthesis |
| topic | Computer Vision and Pattern Recognition Robotics Image and Video Processing I.4.9 |
| url | https://arxiv.org/abs/2507.02993 |