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3D Semi-Landmarks Based Statistical Face Reconstruction
Journal Title CIT. Journal of Computing and Information Technology
Journal Abbreviation CIT
Publisher Group University of Zagreb
Website http://cit.srce.unizg.hr/index.php/CIT
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Title 3D Semi-Landmarks Based Statistical Face Reconstruction
Authors Berar, Maxime; Desvignes, Michel; Bailly, Gerard; Payan, Yohan
Abstract The aim of craniofacial reconstruction is to estimate the shape of a face from the shape of the skull. Few works in computerized assisted facial reconstruction have been provided in the past, probably due to technical (poor machine performances and data availability) and theoretical (complexity) reasons. Therefore, the main published works consist in manual reconstructions. In this paper, an original approach proposes first to build a 3D statistical model of the set skull/face from 3D CT scans. Then, a reconstruction method is introduced in order to estimate, from this statistical model, the 3D facial shape of one subject from known skull data.
Publisher University of Zagreb, University Computing Centre - SRCE
Date 1970-01-01
Source Journal of Computing and Information Technology Vol 14, No 1 (2006): Special Issue on Computer-Assisted Craniofacial Reconstruction and Modeling
Rights CIT. Journal of Computing and Information Technology is an open access journal.Authors who publish with this journal agree to the following terms:Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work´s authorship and initial publication in this journal.Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal´s published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).

 

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