{"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/review-of-statistical-shape-spaces-for-3d-1","title":"Review of Statistical Shape Spaces for 3D Data with ComparativeAnalysis for Human Faces","arxiv_id":null,"date":"2014-04-04","proceeding":null,"authors":["Alan Brunton","Augusto Salazar","Timo Bolkart","Stefanie Wuhrer"],"abstract":"With systems for acquiring 3D surface data being evermore commonplace, it has become important to reliably extract specific shapes from the acquired data.  In the presence of noise and occlusions, this can be done through the use of statistical shape models, which are learned from databases of clean examples of the shape in question.  In this paper, we review,analyze and compare different statistical models:  from those that analyze the variation in geometry globally to those that analyze the variation in geometry locally. We first review how different types of models have been used in the literature, then proceed to define the models and analyze them theoretically,in  terms  of both  their  statistical  and  computational aspects.We then perform extensive experimental comparison on the task of model fitting, and give intuition about which type of model is better for a few applications. Due to the wide avail-ability of databases of high-quality data,  we use the human face as the specific shape we wish to extract from corrupted data.","url_abs":"https://arxiv.org/abs/1209.6491","url_pdf":"https://arxiv.org/pdf/1209.6491.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":"review-of-statistical-shape-spaces-for-3d-1","repo_url":"https://github.com/TimoBolkart/GlobalLocalFaceModels","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"3d-face-modeling","task_name":"3D Face Modelling"},{"task_slug":"face-model","task_name":"Face Model"},{"task_slug":"face-reconstruction","task_name":"Face Reconstruction"}],"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}