{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/predicting-the-next-best-view-for-3d-mesh","title":"Predicting the Next Best View for 3D Mesh Refinement","arxiv_id":"1805.06207","date":"2018-05-16","proceeding":null,"authors":["Luca Morreale","Andrea Romanoni","Matteo Matteucci"],"abstract":"3D reconstruction is a core task in many applications such as robot\nnavigation or sites inspections. Finding the best poses to capture part of the\nscene is one of the most challenging topic that goes under the name of Next\nBest View. Recently, many volumetric methods have been proposed; they choose\nthe Next Best View by reasoning over a 3D voxelized space and by finding which\npose minimizes the uncertainty decoded into the voxels. Such methods are\neffective, but they do not scale well since the underlaying representation\nrequires a huge amount of memory. In this paper we propose a novel mesh-based\napproach which focuses on the worst reconstructed region of the environment\nmesh. We define a photo-consistent index to evaluate the 3D mesh accuracy, and\nan energy function over the worst regions of the mesh which takes into account\nthe mutual parallax with respect to the previous cameras, the angle of\nincidence of the viewing ray to the surface and the visibility of the region.\nWe test our approach over a well known dataset and achieve state-of-the-art\nresults.","url_abs":"http://arxiv.org/abs/1805.06207v1","url_pdf":"http://arxiv.org/pdf/1805.06207v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"predicting-the-next-best-view-for-3d-mesh","repo_url":"https://github.com/luca-morreale/stochastic-nbv-4-mesh-refinement","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"3d-reconstruction","task_name":"3D Reconstruction"},{"task_slug":"robot-navigation","task_name":"Robot Navigation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}