{"id":837,"date":"2026-06-14T20:28:39","date_gmt":"2026-06-14T20:28:39","guid":{"rendered":"https:\/\/home.pf.jcu.cz\/~csgg2026\/index.php\/curvature-guided-graph-and-energy-optimization-for-robust-surface-reconstruction-of-point-clouds\/"},"modified":"2026-06-14T20:28:39","modified_gmt":"2026-06-14T20:28:39","slug":"curvature-guided-graph-and-energy-optimization-for-robust-surface-reconstruction-of-point-clouds","status":"publish","type":"post","link":"https:\/\/home.pf.jcu.cz\/~csgg2026\/index.php\/en\/curvature-guided-graph-and-energy-optimization-for-robust-surface-reconstruction-of-point-clouds\/","title":{"rendered":"Curvature-Guided Graph and Energy Optimization for Robust Surface Reconstruction of Point Clouds"},"content":{"rendered":"<p><em>Sepehr Gholami<\/em><br \/><small>Faculty of Mathematics, Statistics and Computer Science, Department of Computer, University of Tehran, Tehran<\/small><\/p>\n<p>This paper presents a curvature-guided graph and energy optimization framework for robust surface reconstruction from unstructured point clouds. The proposed method addresses challenges caused by noise and non-uniform sampling by integrating curvature-aware geometric modeling with energy-based surface optimization. Our main contributions are threefold. First, we introduce a curvature-guided adaptive graph construction strategy that encodes local geometric structures more faithfully by combining spatial proximity with curvature-sensitive weighting. Second, we propose a novel surface consistency energy that jointly enforces geometric fidelity and smoothness while explicitly preserving sharp features through curvature-aware regularization. Third, we design an efficient iterative optimization scheme that improves reconstruction quality while maintaining computational efficiency. In the first stage, an adaptive k-nearest neighbor graph is constructed using the proposed curvature-aware weighting, followed by an initial mesh generation via a triangulation-based reconstruction scheme. In the second stage, the proposed energy function is minimized iteratively to refine surface consistency and feature preservation. Extensive experiments on synthetic datasets and real-world LiDAR scans demonstrate that the proposed method outperforms classical approaches such as Poisson Surface Reconstruction and Ball Pivoting Algorithm, as well as recent learning-based methods, in terms of Chamfer Distance, normal consistency, and feature preservation, while maintaining competitive computational cost.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Sepehr GholamiFaculty of Mathematics, Statistics and Computer Science, Department of Computer, University of Tehran, Tehran This paper presents a curvature-guided graph and energy optimization framework for robust surface reconstruction from unstructured point clouds. The proposed method addresses challenges caused by noise and non-uniform sampling by integrating curvature-aware geometric modeling with energy-based surface optimization. Our main [&hellip;]<\/p>\n","protected":false},"author":39,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[5],"tags":[],"class_list":["post-837","post","type-post","status-publish","format-standard","hentry","category-presentations"],"_links":{"self":[{"href":"https:\/\/home.pf.jcu.cz\/~csgg2026\/index.php\/wp-json\/wp\/v2\/posts\/837","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/home.pf.jcu.cz\/~csgg2026\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/home.pf.jcu.cz\/~csgg2026\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/home.pf.jcu.cz\/~csgg2026\/index.php\/wp-json\/wp\/v2\/users\/39"}],"replies":[{"embeddable":true,"href":"https:\/\/home.pf.jcu.cz\/~csgg2026\/index.php\/wp-json\/wp\/v2\/comments?post=837"}],"version-history":[{"count":0,"href":"https:\/\/home.pf.jcu.cz\/~csgg2026\/index.php\/wp-json\/wp\/v2\/posts\/837\/revisions"}],"wp:attachment":[{"href":"https:\/\/home.pf.jcu.cz\/~csgg2026\/index.php\/wp-json\/wp\/v2\/media?parent=837"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/home.pf.jcu.cz\/~csgg2026\/index.php\/wp-json\/wp\/v2\/categories?post=837"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/home.pf.jcu.cz\/~csgg2026\/index.php\/wp-json\/wp\/v2\/tags?post=837"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}