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Facial Video Based Response Registration System

J.-L. Dugelay, Usman Saeed
2008 Zenodo  
It gets the rough localization of the mouth region and then performs multiple classical image processing techniques to extract the outer lip contour and finally a support vector machine (SVM) is used to  ...  Finally some have used specialized equipment [15] . Lip Detection / Segmentation Lip detection and segmentation is crucial for lip-reading and model based methods form the core set of techniques.  ... 
doi:10.5281/zenodo.41008 fatcat:rgbmvlhd65gk3cdtrjdht6umdq

An Approach for Efficient Detection of Cephalometric Landmarks

Thuong Le-Tien, Hieu Pham-Chi
2014 Procedia Computer Science  
with the Support Vector Machine (SVM), then utilizing Thresholding and Mathematical Morphological (TMM) algorithm to trace soft tissue profile.  ...  Finally, the landmarks of soft tissue profile and the mandible's edge are pinned based on analyzing the contour plot of these lines. The simulation results have high accuracy.  ...  Acknowledgements: The authors appreciate the NAFOSTED (the National Foundation for Science and Technology Development in Vietnam) for their financial support to present the work at the conference.  ... 
doi:10.1016/j.procs.2014.08.044 fatcat:6352jejkljairmvxbuct4xp5um

The Intersection of the Genetic Architectures of Orofacial Clefts and Normal Facial Variation

Karlijne Indencleef, Hanne Hoskens, Myoung Keun Lee, Julie D. White, Chenxing Liu, Ryan J. Eller, Sahin Naqvi, George L. Wehby, Lina M. Moreno Uribe, Jacqueline T. Hecht, Ross E. Long, Kaare Christensen (+11 others)
2021 Frontiers in Genetics  
This study thus supports the hypothesis of a shared genetic architecture of normal facial development and OFC.  ...  Unaffected relatives of individuals with non-syndromic cleft lip with or without cleft palate (NSCL/P) show distinctive facial features.  ...  of the 63 segments (Figure 1 ) by performing a shape regression.  ... 
doi:10.3389/fgene.2021.626403 pmid:33692830 pmcid:PMC7937973 fatcat:4okmlcn6erfr5jejmeeyfu26yy

Learning Active Shape Models for Bifurcating Contours

M. Seise, S.J. McKenna, I.W. Ricketts, C.A. Wigderowitz
2007 IEEE Transactions on Medical Imaging  
Results are presented using various features, Mahalanobis distance, distance weighted K−nearest neighbours and two relevance vector machine based methods as quality of fit measure.  ...  Statistical shape models are often learned from examples based on landmark correspondences between annotated examples.  ...  Fig. 8 . 8 Effect of K and window size on E and σ E using G-scaled gradient. Fig. 10 . 10 Histogram of segmentation errors Es when using K − N N regression (K = 25, normalised gradient, W = 2).  ... 
doi:10.1109/tmi.2007.895479 pmid:17518061 fatcat:nr5vfdjlujc2lipigix7gxkvuq

Lip-motion events analysis and lip segmentation using optical flow

Stefan M. Karlsson, Josef Bigun
2012 2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops  
Our method is translation and rotation invariant, works at very fast speeds, and does not require segmented lips.  ...  Furthermore, we provide a semi-automatic tool for generating groundtruth segmentation of video data, also based on the optical flow algorithm used for tracking keypoints at faster than 200 frames/second  ...  second order time derivative of outer lip contour area.  ... 
doi:10.1109/cvprw.2012.6239228 dblp:conf/cvpr/KarlssonB12 fatcat:d646l2xmkjf6dk25hx66sim5ce

Mouth features extraction for emotion classification

Adam Wojciechowski, Robert Staniucha
2016 Proceedings of the 2016 Federated Conference on Computer Science and Information Systems  
The paper concentrates on classification of human poses based on mouth.  ...  It is gradient based. Evaluation of the method was performed for a subset of the Yale images database and classification accuracy for single emotion is over 70%.  ...  Kim [28] and Chien [29] analyzed grid-based and coordinate-based lips features (width/height of outer/inner lips edges) for Korean language words recognition support.  ... 
doi:10.15439/2016f390 dblp:conf/fedcsis/WojciechowskiS16 fatcat:33a2hhnzxbf2napw3susp4fjda

Machine Learning Systems for Detecting Driver Drowsiness [chapter]

Esra Vural, Müjdat Çetin, Aytül Erçil, Gwen Littlewort, Marian Bartlett, Javier Movellan
2008 In-Vehicle Corpus and Signal Processing for Driver Behavior  
These measures were passed to learningbased classifiers such as Adaboost and multinomial ridge regression.  ...  Automatic classifiers for 30 facial actions from the Facial Action Coding system were developed using machine learning on a separate database of spontaneous expressions.  ...  Acknowledgements This research was supported in part by NSF grants NSF-CNS 0454233,SBE-0542013 and by a grant from Turkish State Planning Organization.  ... 
doi:10.1007/978-0-387-79582-9_8 fatcat:tztm2hmn2nagbfoqwjpa6hqj7e

Unsupervised segmentation of brain tissue in multivariate MRI

A. Alexandra Constantin, B. Ruzena Bajcsy, C. Sarah Nelson
2010 2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro  
In this paper, we present an unsupervised, automated technique for brain tissue segmentation based on multivariate magnetic resonance (MR) and spectroscopy images, for patients with gliomas.  ...  The healthy brain tissue is then segmented into white matter, gray matter, and cerebrospinal fluid (CSF) using a hierarchical graphical model whose parameters are estimated using the EM algorithm.  ...  Supervised segmentation methods use classification algorithms such as k-nearest-neighbor [3] , Bayes classifier [3] , Neural Networks [3] , and Support Vector Machines (SVMs) [4] , to learn models  ... 
doi:10.1109/isbi.2010.5490406 dblp:conf/isbi/ConstantinBN10 fatcat:iicfvdbqpbeovizwad4i3p5vdy

Face-Based Attention Recognition Model for Children with Autism Spectrum Disorder

Bilikis Banire, Dena Al Thani, Marwa Qaraqe, Bilal Mansoor
2021 Journal of Healthcare Informatics Research  
The first is based on geometric feature transformation using a support vector machine (SVM) classifier, and the second is based on the transformation of time-domain spatial features to 2D spatial images  ...  This paper proposes a face-based attention recognition model using two methods.  ...  Also, we appreciate the support of Mustapha Makki and other institutions: Step-by-Step Center, Renad Academy, Qatar Autism Society, and Texas A & M (US and Qatar campuses).  ... 
doi:10.1007/s41666-021-00101-y pmid:35415454 pmcid:PMC8982782 fatcat:pxlwf2d36vhttflqjhy73fbl2u

Identifying User-Specific Facial Affects from Spontaneous Expressions with Minimal Annotation

Michael Xuelin Huang, Grace Ngai, Kien A. Hua, Stephen C.F. Chan, Hong Va Leong
2016 IEEE Transactions on Affective Computing  
PADMA uses a novel Association-based Multiple Instance Learning (AMIL) method, which learns a personal facial affect model through expression frequency analysis, and does not need expert input or frame-based  ...  PADMA involves a training/calibration phase in which the user watches short video segments and reports the affect that best describes his/her overall feeling throughout the segment.  ...  This work was partially supported by grants PolyU 5235/11E and PolyU 5222/13E from the Hong Kong Research Grants Council.  ... 
doi:10.1109/taffc.2015.2495222 fatcat:6h4d72q3ybcldgate4mmin7obu

Recent developments in visual sign language recognition

Ulrich von Agris, Jörg Zieren, Ulrich Canzler, Britta Bauer, Karl-Friedrich Kraiss
2007 Universal Access in the Information Society  
Since sign languages make use of manual and facial means of expression, both channels are employed for recognition.  ...  In the next processing step, a numerical description of the facial expression, head pose, line of sight, and lip outline is computed.  ...  For ASM initialization the lip borders must be segmented from the image as accurately as possible. 3.5.3.1 Lip region segmentation Segmentation of the lip region makes use of four different feature maps  ... 
doi:10.1007/s10209-007-0104-x fatcat:kdyboduv3jeavoflcfvjocsnia

Efficient quantitative assessment of facial paralysis using iris segmentation and active contour-based key points detection with hybrid classifier

Jocelyn Barbosa, Kyubum Lee, Sunwon Lee, Bilal Lodhi, Jae-Gu Cho, Woo-Keun Seo, Jaewoo Kang
2016 BMC Medical Imaging  
Hybrid classifiers (i.e. rule-based with regularized logistic regression) were employed for discriminating healthy and unhealthy subjects, FP type classification, and for facial paralysis grading based  ...  Combining iris segmentation and key point-based method has several merits that are essential for our real application.  ...  Acknowledgements This work was supported by the National Research Foundation of Korea (NRF) grant (Nos. 2014R1A2A1A10051238 and 2014M3C9A3063543) and research scholarship granted by the National Institute  ... 
doi:10.1186/s12880-016-0117-0 pmid:26968938 pmcid:PMC4788850 fatcat:of7hp6nwo5fbdbo5okyvz2wpli

Real-time facial action unit intensity prediction with regularized metric learning

Jérémie Nicolle, Kévin Bailly, Mohamed Chetouani
2016 Image and Vision Computing  
For solving this task, we propose adapting the Metric Learning for Kernel Regression (MLKR) framework focusing on overfitting issues induced in high-dimensional spaces.  ...  For solving this task, we propose adapting the Metric Learning for Kernel Regression (MLKR) framework focusing on overfitting issues induced in high-dimensional spaces.  ...  In [59] , the authors used Support Vector Regression on Local Binary Pattern (LBP) features and included priors via Markov Random Fields (MRF).  ... 
doi:10.1016/j.imavis.2016.03.004 fatcat:vx5eybtunbe5nkakwcok5zci7i

Predicting Group Contribution Behaviour in a Public Goods Game from Face-to-Face Communication

Ehsan Othman, Frerk Saxen, Dmitri Bershadskyy, Philipp Werner, Ayoub Al-Hamadi, Joachim Weimann
2019 Sensors  
Secondly, the contents of FFC are investigated by categorising strategy-relevant topics and using meta-data.  ...  The proposed automatic facial expressions analysis approach uses a new group activity descriptor and utilises random forest classification.  ...  Model and Feature Selection The results in Figure 2a show that RFc performs much better than Support Vector Machine (SVM) models.  ... 
doi:10.3390/s19122786 fatcat:6amqwdep7jhhtkjnevdvzi5pha

Landmark-Based Facial Feature Construction and Action Unit Intensity Prediction

Jialei Ma, Xiansheng Li, Yuanyuan Ren, Ran Yang, Qichao Zhao, Fu-Kwun Wang
2021 Mathematical Problems in Engineering  
Human face recognition has been widely used in many fields, including biorobots, driver fatigue monitoring, and polygraph tests.  ...  Based on the error analysis of the CE-CLM algorithm, dimension reduction of the constructed features is performed by the principal components analysis (PCA).  ...  [4] predicted the AU intensity using the support vector regression (SVR).  ... 
doi:10.1155/2021/6623239 fatcat:xnzcgnzbujhcnllmi6oy7ip6gy
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