{"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/multi-image-matching-via-fast-alternating","title":"Multi-Image Matching via Fast Alternating Minimization","arxiv_id":"1505.04845","date":"2015-05-19","proceeding":"ICCV 2015 12","authors":["Xiaowei Zhou","Menglong Zhu","Kostas Daniilidis"],"abstract":"In this paper we propose a global optimization-based approach to jointly\nmatching a set of images. The estimated correspondences simultaneously maximize\npairwise feature affinities and cycle consistency across multiple images.\nUnlike previous convex methods relying on semidefinite programming, we\nformulate the problem as a low-rank matrix recovery problem and show that the\ndesired semidefiniteness of a solution can be spontaneously fulfilled. The\nlow-rank formulation enables us to derive a fast alternating minimization\nalgorithm in order to handle practical problems with thousands of features.\nBoth simulation and real experiments demonstrate that the proposed algorithm\ncan achieve a competitive performance with an order of magnitude speedup\ncompared to the state-of-the-art algorithm. In the end, we demonstrate the\napplicability of the proposed method to match the images of different object\ninstances and as a result the potential to reconstruct category-specific object\nmodels from those images.","url_abs":"http://arxiv.org/abs/1505.04845v2","url_pdf":"http://arxiv.org/pdf/1505.04845v2.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":"multi-image-matching-via-fast-alternating","repo_url":"https://github.com/gauzias/sulcal_graphs_matching","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok"}}],"tasks":[{"task_slug":"global-optimization","task_name":"global-optimization"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1505.04845","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}