<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-04-14T04:24:53Z</responseDate><request verb="GetRecord" identifier="oai:www.recercat.cat:10230/72946" metadataPrefix="oai_dc">https://recercat.cat/oai/request</request><GetRecord><record><header><identifier>oai:recercat.cat:10230/72946</identifier><datestamp>2026-04-08T14:49:33Z</datestamp><setSpec>com_2072_6</setSpec><setSpec>col_2072_452952</setSpec></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:doc="http://www.lyncode.com/xoai" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
   <dc:title>BabyFM: towards accurate 3D baby facial models using spectral decomposition and asymmetry swapping</dc:title>
   <dc:creator>Morales Muñoz, Maria Araceli</dc:creator>
   <dc:creator>Alomar Adrover, Antònia</dc:creator>
   <dc:creator>Porras Pérez, Antonio Reyes</dc:creator>
   <dc:creator>Linguraru, Marius George</dc:creator>
   <dc:creator>Piella Fenoy, Gemma</dc:creator>
   <dc:creator>Sukno, Federico Mateo</dc:creator>
   <dc:subject>3D morphable model</dc:subject>
   <dc:subject>Statistical shape model</dc:subject>
   <dc:subject>Baby facial shape</dc:subject>
   <dc:subject>Spectral correspondences</dc:subject>
   <dc:subject>Asymmetry swapping</dc:subject>
   <dc:description>In this paper, we present the first publicly available 3D statistical facial shape model of babies, the Baby Face Model (BabyFM). Constructing a model of the facial geometry of babies entails specific challenges, such as occlusions, extreme and uncontrollable expressions, and data shortage. We address these challenges by proposing (1) a non-template dependent method that jointly estimates a 3D facial baby-specific template and the point-to-point correspondences; (2) a novel method to establish correspondences based on the spectral decomposition of the Laplace Beltrami Operator, which provides a more robust theoretical foundation than state-of-the-art methods; and (3) an asymmetry-swapping strategy to alleviate the shortage of large scale datasets by decoupling the identity-related and the asymmetry-related shape deformation fields. The latter leads to a data augmentation technique that we integrate within the Gaussian Process Morphable Model framework, providing a simple way of combining synthetic or sample covariance functions. We exhaustively evaluate each stage of our method and demonstrate that (1) when aiming at the 3D facial geometry of a baby, a specific model of babies is needed, since the pre-built publicly available models constructed with adults or older children are not able to accurately represent the facial shape of babies; (2) our spectral approach improves correspondences accuracy with respect to state-of-the-art-methods; and (3) the proposed data augmentation technique enhances the robustness of the BabyFM.</dc:description>
   <dc:description>This work is partly supported by MICIU/AEI/10.13039/501100011033/ under the project grant PID2020-114083GB-I00 and PRE2021-097544 scholarship, the ICREA Academia programme and the NIH Eunice Kennedy Shriver National Institute of Child Health &amp;amp; Human Development grant R42 HD08171203.</dc:description>
   <dc:date>2026-03-31T08:30:00Z</dc:date>
   <dc:date>2026-03-31T08:30:00Z</dc:date>
   <dc:date>2025</dc:date>
   <dc:date>2026-03-31T08:29:59Z</dc:date>
   <dc:type>info:eu-repo/semantics/article</dc:type>
   <dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
   <dc:identifier>Morales Muñoz MA, Alomar Adrover A, Porras Pérez AR, Linguraru MG, Piella Fenoy G, Sukno FM. BabyFM: towards accurate 3D baby facial models using spectral decomposition and asymmetry swapping. Comput Biol Med. 2025 Mar;186:109652. DOI: 10.1016/j.compbiomed.2025.109652</dc:identifier>
   <dc:identifier>0010-4825</dc:identifier>
   <dc:identifier>https://hdl.handle.net/10230/72946</dc:identifier>
   <dc:identifier>http://dx.doi.org/10.1016/j.compbiomed.2025.109652</dc:identifier>
   <dc:language>eng</dc:language>
   <dc:relation>Computers in Biology and Medicine. 2025 Mar;186:109652</dc:relation>
   <dc:relation>info:eu-repo/grantAgreement/ES/2PE/PID2020-114083GB-I00</dc:relation>
   <dc:rights>© 2025 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).</dc:rights>
   <dc:rights>http://creativecommons.org/licenses/by-nc-nd/4.0/</dc:rights>
   <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
   <dc:format>application/pdf</dc:format>
   <dc:format>application/pdf</dc:format>
   <dc:publisher>Elsevier</dc:publisher>
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