Towards a Complete 3D Morphable Model of the Human Head
Three-dimensional morphable models (3DMMs) are powerful statistical tools for representing the 3D shapes and textures of an object class. Here we present the most complete 3DMM of the human head to date that includes face, cranium, ears, eyes, teeth and tongue. To achieve this, we propose two method...
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| Vydáno v: | IEEE transactions on pattern analysis and machine intelligence Ročník 43; číslo 11; s. 4142 - 4160 |
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| Jazyk: | angličtina |
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IEEE
01.11.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
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| ISSN: | 0162-8828, 1939-3539, 2160-9292, 1939-3539 |
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| Abstract | Three-dimensional morphable models (3DMMs) are powerful statistical tools for representing the 3D shapes and textures of an object class. Here we present the most complete 3DMM of the human head to date that includes face, cranium, ears, eyes, teeth and tongue. To achieve this, we propose two methods for combining existing 3DMMs of different overlapping head parts: (i). use a regressor to complete missing parts of one model using the other, and (ii). use the Gaussian Process framework to blend covariance matrices from multiple models. Thus, we build a new combined face-and-head shape model that blends the variability and facial detail of an existing face model (the LSFM) with the full head modelling capability of an existing head model (the LYHM). Then we construct and fuse a highly-detailed ear model to extend the variation of the ear shape. Eye and eye region models are incorporated into the head model, along with basic models of the teeth, tongue and inner mouth cavity. The new model achieves state-of-the-art performance. We use our model to reconstruct full head representations from single, unconstrained images allowing us to parameterize craniofacial shape and texture, along with the ear shape, eye gaze and eye color. |
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| AbstractList | Three-dimensional morphable models (3DMMs) are powerful statistical tools for representing the 3D shapes and textures of an object class. Here we present the most complete 3DMM of the human head to date that includes face, cranium, ears, eyes, teeth and tongue. To achieve this, we propose two methods for combining existing 3DMMs of different overlapping head parts: (i). use a regressor to complete missing parts of one model using the other, and (ii). use the Gaussian Process framework to blend covariance matrices from multiple models. Thus, we build a new combined face-and-head shape model that blends the variability and facial detail of an existing face model (the LSFM) with the full head modelling capability of an existing head model (the LYHM). Then we construct and fuse a highly-detailed ear model to extend the variation of the ear shape. Eye and eye region models are incorporated into the head model, along with basic models of the teeth, tongue and inner mouth cavity. The new model achieves state-of-the-art performance. We use our model to reconstruct full head representations from single, unconstrained images allowing us to parameterize craniofacial shape and texture, along with the ear shape, eye gaze and eye color. Three-dimensional morphable models (3DMMs) are powerful statistical tools for representing the 3D shapes and textures of an object class. Here we present the most complete 3DMM of the human head to date that includes face, cranium, ears, eyes, teeth and tongue. To achieve this, we propose two methods for combining existing 3DMMs of different overlapping head parts: (i). use a regressor to complete missing parts of one model using the other, and (ii). use the Gaussian Process framework to blend covariance matrices from multiple models. Thus, we build a new combined face-and-head shape model that blends the variability and facial detail of an existing face model (the LSFM) with the full head modelling capability of an existing head model (the LYHM). Then we construct and fuse a highly-detailed ear model to extend the variation of the ear shape. Eye and eye region models are incorporated into the head model, along with basic models of the teeth, tongue and inner mouth cavity. The new model achieves state-of-the-art performance. We use our model to reconstruct full head representations from single, unconstrained images allowing us to parameterize craniofacial shape and texture, along with the ear shape, eye gaze and eye color.Three-dimensional morphable models (3DMMs) are powerful statistical tools for representing the 3D shapes and textures of an object class. Here we present the most complete 3DMM of the human head to date that includes face, cranium, ears, eyes, teeth and tongue. To achieve this, we propose two methods for combining existing 3DMMs of different overlapping head parts: (i). use a regressor to complete missing parts of one model using the other, and (ii). use the Gaussian Process framework to blend covariance matrices from multiple models. Thus, we build a new combined face-and-head shape model that blends the variability and facial detail of an existing face model (the LSFM) with the full head modelling capability of an existing head model (the LYHM). Then we construct and fuse a highly-detailed ear model to extend the variation of the ear shape. Eye and eye region models are incorporated into the head model, along with basic models of the teeth, tongue and inner mouth cavity. The new model achieves state-of-the-art performance. We use our model to reconstruct full head representations from single, unconstrained images allowing us to parameterize craniofacial shape and texture, along with the ear shape, eye gaze and eye color. Three-dimensional Morphable Models (3DMMs) are powerful statistical tools for representing the 3D shapes and textures of an object class. Here we present the most complete 3DMM of the human head to date that includes face, cranium, ears, eyes, teeth and tongue. To achieve this, we propose two methods for combining existing 3DMMs of different overlapping head parts: i. use a regressor to complete missing parts of one model using the other, ii. use the Gaussian Process framework to blend covariance matrices from multiple models. Thus we build a new combined face-and-head shape model that blends the variability and facial detail of an existing face model (the LSFM) with the full head modelling capability of an existing head model (the LYHM). Then we construct and fuse a highly-detailed ear model to extend the variation of the ear shape. Eye and eye region models are incorporated into the head model, along with basic models of the teeth, tongue and inner mouth cavity. The new model achieves state-of-the-art performance. We use our model to reconstruct full head representations from single, unconstrained images allowing us to parameterize craniofacial shape and texture, along with the ear shape, eye gaze and eye color. |
| Author | Ploumpis, Stylianos Sullivan, Eimear Oa Smith, William A. P. Ververas, Evangelos Moschoglou, Stylianos Pears, Nick Wang, Haoyang Zafeiriou, Stefanos Gecer, Baris |
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| References_xml | – ident: ref58 doi: 10.1109/FG.2017.79 – start-page: 1 year: 2015 ident: ref10 article-title: Discriminative 3D morphable model fitting publication-title: Proc 11th IEEE Int Conf Workshops Autom Face Gesture Recognit – ident: ref50 doi: 10.1109/FG.2018.00064 – ident: ref33 doi: 10.1109/TPAMI.2009.30 – year: 2019 ident: ref15 article-title: 3D morphable face models-past, present and future – ident: ref35 doi: 10.1007/978-3-030-01261-8_44 – ident: ref5 doi: 10.1111/j.1467-8659.2009.01373.x – ident: ref64 doi: 10.1109/TPAMI.2014.2313123 – ident: ref34 doi: 10.1109/CVPR.2015.7299081 – year: 2008 ident: ref54 publication-title: Statistical Models of Shape Optimisation and Evaluation – ident: ref17 doi: 10.1145/311535.311556 – ident: ref56 doi: 10.1109/ICCV.2015.411 – ident: ref48 doi: 10.1016/j.patcog.2017.09.006 – ident: ref46 doi: 10.1109/TPAMI.2017.2739743 – ident: ref27 doi: 10.1109/CVPR.2018.00767 – ident: ref1 doi: 10.1109/TPAMI.2003.1227983 – ident: ref14 doi: 10.1109/ICCV.2017.335 – ident: ref40 doi: 10.1145/2431211.2431221 – year: 2002 ident: ref30 article-title: Civilian American and European surface anthropometry resource (CAESAR). Volume 2: Descriptions – ident: ref20 doi: 10.1109/CVPR.2016.598 – ident: ref23 doi: 10.1109/CVPR.2019.00125 – ident: ref24 doi: 10.1007/s11263-019-01151-x – ident: ref44 doi: 10.1109/FG.2018.00065 – ident: ref57 doi: 10.1007/978-3-319-46475-6_23 – year: 2019 ident: ref52 article-title: 3DFaceGAN: Adversarial nets for 3D face representation, generation, and translation – ident: ref22 doi: 10.1109/CVPR.2017.580 – ident: ref9 doi: 10.5220/0005669500790086 – ident: ref28 doi: 10.1109/CVPR.2017.163 – ident: ref32 doi: 10.1145/3130800.31310887 – ident: ref11 doi: 10.1109/CVPR.2016.23 – ident: ref31 doi: 10.1007/978-3-030-01219-9_43 – ident: ref62 doi: 10.1109/CVPR.2015.7299081 – ident: ref26 doi: 10.1109/CVPR.2019.00122 – ident: ref29 doi: 10.1145/3130800.3130813 – ident: ref7 doi: 10.1145/3130800.3130883 – ident: ref25 doi: 10.1109/FG.2018.00027 – ident: ref55 doi: 10.1016/j.cviu.2014.05.005 – ident: ref12 doi: 10.1007/3-540-44887-X_8 – start-page: 276 year: 2010 ident: ref21 article-title: Optimal regions for linear model-based 3D face reconstruction publication-title: Proc Asian Conf Comput Vis – ident: ref43 doi: 10.1109/ICASSP.2016.7471981 – ident: ref37 doi: 10.1145/2661229.2661285 – ident: ref61 doi: 10.1145/2578153.2578190 – ident: ref41 doi: 10.1007/s11263-011-0436-0 – ident: ref51 doi: 10.1109/CVPRW.2017.250 – ident: ref3 doi: 10.1109/TPAMI.2012.206 – ident: ref47 doi: 10.1109/FG.2018.00021 – ident: ref65 doi: 10.1109/ICPR.2014.210 – start-page: 787 year: 2015 ident: ref13 article-title: High-fidelity pose and expression normalization for face recognition in the wild publication-title: Proc IEEE Conf Comput Vis Pattern Recognit – ident: ref45 doi: 10.1109/TMM.2013.2282134 – ident: ref59 doi: 10.1007/s11263-008-0152-6 – ident: ref2 doi: 10.1007/978-3-319-46484-8_5 – ident: ref42 doi: 10.1117/12.849965 – ident: ref19 doi: 10.1109/CVPR.2007.383165 – ident: ref60 doi: 10.1007/978-3-319-46448-0_18 – ident: ref53 doi: 10.1109/CVPR.2018.00917 – ident: ref38 doi: 10.1007/978-3-319-46448-0_18 – ident: ref16 doi: 10.1109/CVPR.2019.01119 – ident: ref18 doi: 10.1109/AVSS.2009.58 – ident: ref6 doi: 10.1145/882262.882311 – ident: ref4 doi: 10.1016/j.jcms.2015.02.005 – ident: ref63 doi: 10.1109/CVPR.2014.235 – ident: ref39 doi: 10.1049/iet-bmt.2011.0003 – ident: ref36 doi: 10.1145/2897824.2925962 – ident: ref8 doi: 10.1109/CVPR.2018.00868 – ident: ref49 doi: 10.1109/TMM.2013.2282134 |
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| SubjectTerms | 3D reconstruction 3DMM Computational modeling Covariance matrix craniofacial 3DMM Cranium Ear Eye movements Face Gaussian process Head Image reconstruction Magnetic heads morphable model combination Shape Three dimensional models Three-dimensional displays Tongue |
| Title | Towards a Complete 3D Morphable Model of the Human Head |
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