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Fitting 3D Morphable Face Models using local features

Patrik Huber, Zhen-Hua Feng, William Christmas, Josef Kittler, Matthias Ratsch
<span title="">2015</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/anlh4tvwprcrtoxv5d4h6a7rye" style="color: black;">2015 IEEE International Conference on Image Processing (ICIP)</a> </i> &nbsp;

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<span title="2015-03-08">2015</span> <span class="release-stage" >pre-print</span> <span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1503.02330v1">arXiv:1503.02330v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/zpmilz7sone45c3gho23wbr25y">fatcat:zpmilz7sone45c3gho23wbr25y</a> </span>
In this paper, we propose a novel fitting method that uses local image features to fit a 3D Morphable Model to 2D images.  ...  Our approach is unique in that we are the first to use local features to fit a Morphable Model. Because of the speed of our method, it is applicable for realtime applications.  ...  CONCLUSION We proposed a new way to fit 3D Morphable Models that uses local image features.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/icip.2015.7350989">doi:10.1109/icip.2015.7350989</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/icip/HuberFCKR15.html">dblp:conf/icip/HuberFCKR15</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/vz32ebflmrcolderfd3swc5ytu">fatcat:vz32ebflmrcolderfd3swc5ytu</a> </span>
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Citation

Patrik Huber, Zhen-Hua Feng, William Christmas, Josef Kittler, Matthias Ratsch. "Fitting 3D Morphable Face Models using local features." 2015 IEEE International Conference on Image Processing (ICIP) (2015) 1195-1199

FACIAL FEATURE EXTRACTION FROM RANGE IMAGES USING A 3D MORPHABLE MODEL

Mi Lu
<span title="2021-03-11">2021</span> <i title="figshare"> figshare.com </i> &nbsp;

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Unlike previous methods that fit a 3D morphable model to 2D intensity images, our scheme utilizes 3D range images to extract features without requiring manually-defined initial landmark points.  ...  A linear transformation is used to achieve the mapping between the 3D model and a 3D range image, which makes the computation simple and fast.  ...  FEATURE EXTRACTION FROM RANGE IMAGES The key step of our feature extraction method is to fit the 3D morphable model to an input 3D range image.  ... 
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Citation

Mi Lu. "FACIAL FEATURE EXTRACTION FROM RANGE IMAGES USING A 3D MORPHABLE MODEL." figshare.com (2021)

Automatic bootstrapping of a morphable face model using multiple components

Frank B. ter Haar, Remco C. Veltkamp
<span title="">2009</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/6s36fqp6q5hgpdq2scjq3sfu6a" style="color: black;">2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops</a> </i> &nbsp;

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Our algorithm is based on a morphable model fitting method that uses a set of predefined face components. This fitting method produces accurate model fits to 3D face data with noise and holes.  ...  We present a new bootstrapping algorithm to automatically enhance a 3D morphable face model with new face data.  ...  The authors thank the University of South Florida for providing the USF Human ID 3D Database and the morphable face model, University of Notre Dame for the UND set, Binghamton University for the BU-3DFE  ... 
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Frank B. ter Haar, Remco C. Veltkamp. "Automatic bootstrapping of a morphable face model using multiple components." 2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops (2009) 1497-1504

Expression modeling for expression-invariant face recognition

Frank B. ter Haar, Remco C. Veltkamp
<span title="">2010</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/eu2m4gixpvbj3bgkrmcfu4ezdi" style="color: black;">Computers &amp; graphics</a> </i> &nbsp;

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The two main difficulties are (1) how to build a new morphable face model that deals with expressions, and (2) how to fit this morphable face model automatically to new 3D face scans with unknown expressions  ...  Morphable face models have proven to be an effective tool for 3D face modeling and face recognition, but the extension to 3D face scans with expressions is still a challenge.  ...  More local minima can be used at the cost of a larger feature vector.  ... 
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Citation

Frank B. ter Haar, Remco C. Veltkamp. "Expression modeling for expression-invariant face recognition." Computers & graphics 34.3 (2010) 231-241

Detecting Acromegaly: Screening for Disease with a Morphable Model [chapter]

Erik Learned-Miller, Qifeng Lu, Angela Paisley, Peter Trainer, Volker Blanz, Katrin Dedden, Ralph Miller
<span title="">2006</span> <i title="Springer Berlin Heidelberg"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2w3awgokqne6te4nvlofavy5a4" style="color: black;">Lecture Notes in Computer Science</a> </i> &nbsp;

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The model parameters capture many features of the 3D shape of the subject's head from just a single photograph, and are used directly for classification.  ...  We modelled each subject's face in an analysis-by-synthesis loop using the three-dimensional morphable face model of Blanz and Vetter.  ...  To intialize the model fitting process, the user clicks on a number (seven to 12) of feature points in the image and the corresponding features on the 3D model using an interactive tool.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/11866763_61">doi:10.1007/11866763_61</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/mkcm7wfvlff45b7wkgvdvfdu2m">fatcat:mkcm7wfvlff45b7wkgvdvfdu2m</a> </span>
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Citation

Erik Learned-Miller, Qifeng Lu, Angela Paisley, Peter Trainer, Volker Blanz, Katrin Dedden, Ralph Miller. "Detecting Acromegaly: Screening for Disease with a Morphable Model." Lecture Notes in Computer Science (2006) 495-503

3D morphable face models revisited

Ankur Patel, William A. P. Smith
<span title="">2009</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ilwxppn4d5hizekyd3ndvy2mii" style="color: black;">2009 IEEE Conference on Computer Vision and Pattern Recognition</a> </i> &nbsp;

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In this paper we revisit the process of constructing a high resolution 3D morphable model of face shape variation.  ...  As an example application of this improved model, we show how it may be fitted to a sparse set of 2D feature points (approximately 100).  ...  [13] have begun to consider the problem of model dominance and used local feature analysis to locally improve the fit of the model to a set of sparse feature points.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/cvpr.2009.5206522">doi:10.1109/cvpr.2009.5206522</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/cvpr/PatelS09.html">dblp:conf/cvpr/PatelS09</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/we72zwao5bbr3aesgreezh5sh4">fatcat:we72zwao5bbr3aesgreezh5sh4</a> </span>
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Citation

Ankur Patel, William A. P. Smith. "3D morphable face models revisited." 2009 IEEE Conference on Computer Vision and Pattern Recognition (2009) 1327-1334

3D Face Modeling Based On 3D Dense Morphable Face Shape Model

Yongsuk Jang Kim, Sun-Tae Chung, Boogyun Kim, Seongwon Cho
<span title="2008-01-21">2008</span> <i title="Zenodo"> Zenodo </i> &nbsp;

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Then, the proposed method obtains a 3D dense shape model of the face to be modeled by fitting the constructed 3D dense morphable shape model into the reconstructed 3D vertices.  ...  The proposed 3D modeling method first constructs a 3D dense morphable shape model from 3D face scan data obtained using a 3D scanner.  ...  Next, this 3D face modeling method obtains a 3D face shape model of the person to be modeled by fitting 3D morphable shape model into the 3D surface mesh.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5281/zenodo.1054922">doi:10.5281/zenodo.1054922</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/6y6y57ewzvdefn6fxj23mndcsy">fatcat:6y6y57ewzvdefn6fxj23mndcsy</a> </span>
<span class="ui label basic orange small" title="Open Access">Open Access</span>
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Citation

Yongsuk Jang Kim, Sun-Tae Chung, Boogyun Kim, Seongwon Cho. "3D Face Modeling Based On 3D Dense Morphable Face Shape Model." Zenodo (2008)

3D Face Reconstruction Techniques: Passive Methods

<span title="2019-07-30">2019</span> <i title="Blue Eyes Intelligence Engineering and Sciences Engineering and Sciences Publication - BEIESP"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/3sfifsouvjgadp4gfj54u3z2ku" style="color: black;">International journal of recent technology and engineering</a> </i> &nbsp;

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The databases used in the recent works are discussed and the performance evaluation of methods on different databases is analyzed.  ...  Passive methods, used by different researchers are analyzed and their effects on different parameters are discussed in this work.  ...  Here apart from other works cylindrical head model was used, from the know feature points, the occluded points are estimated by 3D model fitting.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.35940/ijrte.b3152.078219">doi:10.35940/ijrte.b3152.078219</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/5x2422hs45bgfcl43qreodsgzu">fatcat:5x2422hs45bgfcl43qreodsgzu</a> </span>
<span class="ui label basic orange small" title="Open Access">Open Access</span>
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"3D Face Reconstruction Techniques: Passive Methods." International journal of recent technology and engineering 8.2 (2019) 4354-4364

What computational model provides the best explanation of face representations in the primate brain? [article]

Le Chang, Bernhard Egger, Thomas Vetter, Doris Tsao
<span title="2020-06-08">2020</span> <i title="Cold Spring Harbor Laboratory"> bioRxiv </i> &nbsp; <span class="release-stage" >pre-print</span>

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A previous study reported that single face patch neurons encode axes of a generative model called the 'active appearance' model (Chang and Tsao, 2017), which transforms 50-d feature vectors separately  ...  However, it remains unclear whether this model constitutes the best model for explaining face cell responses.  ...  C, To create facial images without hair, each facial image in the database was fit using a 3D Morphable Model (left). The fits were used as inputs to each model.  ... 
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<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210715032411/https://www.biorxiv.org/content/biorxiv/early/2021/03/30/2020.06.07.111930.full.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/46/ae/46ae1a7910063c31c55477fc1e6509866131150c.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1101/2020.06.07.111930"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> biorxiv.org </button> </a>
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Le Chang, Bernhard Egger, Thomas Vetter, Doris Tsao. "What computational model provides the best explanation of face representations in the primate brain?." bioRxiv (2020)

3D Face Model Fitting for Recognition [chapter]

Frank B. ter Haar, Remco C. Veltkamp
<span title="">2008</span> <i title="Springer Berlin Heidelberg"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2w3awgokqne6te4nvlofavy5a4" style="color: black;">Lecture Notes in Computer Science</a> </i> &nbsp;

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In a global to local fitting scheme, the shape parameters of this model are optimized such that the produced instance of the model accurately fits the 3D scan data of the input face.  ...  This paper presents an automatic efficient method to fit a statistical deformation model of the human face to 3D scan data.  ...  The authors thank the University of South Florida for providing the USF Human ID 3D Database.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-540-88693-8_48">doi:10.1007/978-3-540-88693-8_48</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/hugjjzcfrvh5zoa6y6tezmf6xm">fatcat:hugjjzcfrvh5zoa6y6tezmf6xm</a> </span>
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Frank B. ter Haar, Remco C. Veltkamp. "3D Face Model Fitting for Recognition." Lecture Notes in Computer Science (2008) 652-664

3D morphable model construction for robust ear and face recognition

John D. Bustard, Mark S. Nixon
<span title="">2010</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ilwxppn4d5hizekyd3ndvy2mii" style="color: black;">2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition</a> </i> &nbsp;

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The paper describes work that investigates this hypothesis using an approach based on the construction of a 3D morphable model of the head and ear.  ...  When combined with a robust registration algorithm the resulting system enables full head morphable models to be constructed efficiently using less constrained datasets.  ...  The algorithms used in this paper are available through the project website [9] . Related work In 1999, Blanz and Vetter created the first 3D morphable model [7] .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/cvpr.2010.5539968">doi:10.1109/cvpr.2010.5539968</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/cvpr/BustardN10.html">dblp:conf/cvpr/BustardN10</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/5h5pg3qs3rgadps7lx5gz66y2i">fatcat:5h5pg3qs3rgadps7lx5gz66y2i</a> </span>
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Citation

John D. Bustard, Mark S. Nixon. "3D morphable model construction for robust ear and face recognition." 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (2010) 2582-2589

A 3D Morphable Eye Region Model for Gaze Estimation [chapter]

Erroll Wood, Tadas Baltrušaitis, Louis-Philippe Morency, Peter Robinson, Andreas Bulling
<span title="">2016</span> <i title="Springer International Publishing"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2w3awgokqne6te4nvlofavy5a4" style="color: black;">Lecture Notes in Computer Science</a> </i> &nbsp;

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The fitted eyeball pose parameters are then used to estimate gaze direction.  ...  We present a new multi-part model of the eye that includes a morphable model of the facial eye region, as well as an anatomy-based eyeball model.  ...  Related Work 3D Morphable Models A 3D morphable model is a statistically-derived generative model, parameterized by shape and texture coefficients.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-319-46448-0_18">doi:10.1007/978-3-319-46448-0_18</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/dm362rpktffvrb3we6krxsqsmu">fatcat:dm362rpktffvrb3we6krxsqsmu</a> </span>
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Citation

Erroll Wood, Tadas Baltrušaitis, Louis-Philippe Morency, Peter Robinson, Andreas Bulling. "A 3D Morphable Eye Region Model for Gaze Estimation." Lecture Notes in Computer Science (2016) 297-313

2D face pose normalisation using a 3D morphable model

J.R. Tena, R.S. Smith, M. Hamouz, J. Kittler, A. Hilton, J. Illingworth
<span title="">2007</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/s4u3jxdcmrevzj46e7ani77j4u" style="color: black;">2007 IEEE Conference on Advanced Video and Signal Based Surveillance</a> </i> &nbsp;

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To measure the effect, we use a state of the art 2D recognition algorithm. The pose correction is performed by means of 3D morphable model.  ...  Pose Normalization Using a 3D Morphable Model By fitting a 3D morphable model to a 2D face image, it becomes possible to render virtual views from the face from different angles.  ...  [14, 9] use a 3D morphable model that is semi-automatically matched to a probe images.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/avss.2007.4425285">doi:10.1109/avss.2007.4425285</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/avss/TenaSHKHI07.html">dblp:conf/avss/TenaSHKHI07</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/vv43xy5ntjdp3bznvpwc752dmm">fatcat:vv43xy5ntjdp3bznvpwc752dmm</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170610065323/http://www.ee.surrey.ac.uk:80/CVSSP/Publications/papers/tena-avss-2007.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/c5/c3/c5c351b094cb1edfc28f90bcdad599ee5411f4f0.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/avss.2007.4425285"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>
Citation

J.R. Tena, R.S. Smith, M. Hamouz, J. Kittler, A. Hilton, J. Illingworth. "2D face pose normalisation using a 3D morphable model." 2007 IEEE Conference on Advanced Video and Signal Based Surveillance (2007) 51-56

Improved 3D assisted pose-invariant face recognition

Liting Wang, Liu Ding, Xiaoqing Ding, Chi Fang
<span title="">2009</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/rc5jnc4ldvhs3dswicq5wk3vsq" style="color: black;">2009 IEEE International Conference on Acoustics, Speech and Signal Processing</a> </i> &nbsp;

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For each sample, a 3D face is constructed by using 3D Morphable Model (3DMM).  ...  In this paper, we locate 88 sparse points from the 2D face sample by automatic face fitting and use their correspondence in the 3D face as shape constraint.  ...  They presented a 3D face reconstruction algorithm by using 3D morphable model.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/icassp.2009.4959727">doi:10.1109/icassp.2009.4959727</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/icassp/WangDDF09.html">dblp:conf/icassp/WangDDF09</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/r5il2cbejbht7gst2uz7tiigx4">fatcat:r5il2cbejbht7gst2uz7tiigx4</a> </span>
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Citation

Liting Wang, Liu Ding, Xiaoqing Ding, Chi Fang. "Improved 3D assisted pose-invariant face recognition." 2009 IEEE International Conference on Acoustics, Speech and Signal Processing (2009) 889-892

Fitting a 3D Morphable Model to Edges: A Comparison Between Hard and Soft Correspondences [chapter]

Anil Bas, William A. P. Smith, Timo Bolkart, Stefanie Wuhrer
<span title="">2017</span> <i title="Springer International Publishing"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2w3awgokqne6te4nvlofavy5a4" style="color: black;">Lecture Notes in Computer Science</a> </i> &nbsp;

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<span title="2016-02-02">2016</span> <span class="release-stage" >pre-print</span>
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1602.01125v1">arXiv:1602.01125v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/mesdydypnjff7pjgngsuzfazha">fatcat:mesdydypnjff7pjgngsuzfazha</a> </span>
<span title="2016-10-03">2016</span> <span class="release-stage">accepted</span>
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1602.01125v2">arXiv:1602.01125v2</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/niiq3pvobrhdlj2qqpp5r4bqsy">fatcat:niiq3pvobrhdlj2qqpp5r4bqsy</a> </span>
We propose a fully automatic method for fitting a 3D morphable model to single face images in arbitrary pose and lighting.  ...  Our approach relies on geometric features (edges and landmarks) and, inspired by the iterated closest point algorithm, is based on computing hard correspondences between model vertices and edge pixels.  ...  Instead of landmarks, local features can be used to aid the morphable model fitting [15] .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-319-54427-4_28">doi:10.1007/978-3-319-54427-4_28</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/6qrtruk2kzdcjgq3wlgo4wnlmq">fatcat:6qrtruk2kzdcjgq3wlgo4wnlmq</a> </span>
<span class="ui label basic blue small">Multiple Versions</span>
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Anil Bas, William A. P. Smith, Timo Bolkart, Stefanie Wuhrer. "Fitting a 3D Morphable Model to Edges: A Comparison Between Hard and Soft Correspondences." Lecture Notes in Computer Science (2017) 377-391

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