{"ID":2899806,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2507.02993","arxiv_id":"2507.02993","title":"Enabling Robust, Real-Time Verification of Vision-Based Navigation through View Synthesis","abstract":"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.","short_abstract":"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 sy...","url_abs":"https://arxiv.org/abs/2507.02993","url_pdf":"https://arxiv.org/pdf/2507.02993v1","authors":"[\"Marius Neuhalfen\",\"Jonathan Grzymisch\",\"Manuel Sanchez-Gestido\"]","published":"2025-07-01T19:47:04Z","proceeding":"cs.CV","tasks":"[\"cs.CV\",\"cs.RO\",\"eess.IV\"]","methods":"[]","has_code":false}