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eSCANFace: Early Screening of Craniofacial Anomalies in Newborn Faces |
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Craniofacial anomalies have been highlighted as an index of developmental disturbance at early stages of life. Initial diagnosis is often based on visual inspection from pediatricians but, unfortunately, dysmorphology is hard to identify in this way, and massive genetic screening is expensive and impractical. For these reasons, there is a growing interest in using facial imaging as a lowcost tool for genetic pre-screening, i.e., to highlight suspicious cases for further study. The objectives of eSCANFace are to develop the technology necessary to make such early screening more accurate, more accessible, and more comprehensive, and to allow its deployment as early as possible in life. |
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Project funded by the Ministry of
Science, Innovation and Universities, who funded this project through grant
PID2020-114083GB-I00 |
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Because dysmorphology patterns tend to be subtle in most disorders, and they can affect any of the spatial components of the face (rightleft, cranio-caudal, anterior-posterior), the main hypothesis in this project is that advanced 3D modeling techniques can lead to a more accurate characterization and screening of craniofacial anomalies in infants and fetuses. This hypothesis is supported by previous findings highlighting that 3D analysis of facial dysmorphology is superior to 2D analysis, both from the project team and from other researchers. For more
information see: http://fsukno.atspace.eu/eScanFace.htm |
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The UNFACE
project addresses fine grained facial analysis with the goal of decoding
hidden facial information. The human face is a fundamental source of
information to understand the behavior of
individuals. Traditionally this has been exploited in computer vision for the
recognition of identity and expressions, but it has been recently suggested
that the information that could be extracted from the face goes well beyond
this and can be indicative of things such as deception, heart rate,
psychological states or even psychiatric disorders such as autism or
depression. Some of this information, however, might be not apparent or it might even be hidden to us, and it could only be recovered by means of specialized techniques. An iconic example is the detection of cardiac heart rate by amplifying the subtle color changes of the face due to the blood flow, which are invisible to the human eye. For more information, please visit the project page: |
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Project TIN2017-90124-P Excelence 2017
call from the Spanish Program for Science and Technology |
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KRISTINA is an EU funded research project, which aims at developing technologies for a human-like socially competent and communicative agent. It runs on mobile communication devices and serves for migrants with language and cultural barriers in the host country. KRISTINA’s overall objective is to research and develop technologies for a human-like socially competent and communicative agent that is run on mobile communication devices and that serves for migrants with language and cultural barriers in the host country as a trusted information provision party and mediator in questions related to basic care and healthcare. KRISTINA will advance the state of the art in dialogue management, multimodal (vocal, facial and gestural) communication analysis and multimodal communication. The technologies will be validated in two use cases, in which prolonged trials will be carried out for each prototype that marks the termination of a SW development cycle, with a representative number of migrants recruited as users from the migration circles identified as especially in need: elderly Turkish migrants and their relatives and short term Polish care giving personnel in Germany and North African migrants in Spain. More information available at: |
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The SP-MORPH
project addresses the analysis of facial geometry for the quantification of
craniofacial Dysmorphology, motivated by: 1) its association with, and
ability to inform on, diseases of early brain development, such as Down
syndrome, fetal alcohol syndrome and schizophrenia; 2) increasing
availability of three-dimensional (3D) imaging technologies that overcome
many of the limitations inherent to two-dimensional approaches. We focus on the development of algorithms for automated and highly accurate analysis of facial surfaces in 3D, with special interest in techniques based on spectral decomposition methods. As opposed to traditional methods, based on a reduced set of landmark points, spectral mesh processing (SMP) allows analysis of the whole facial surface. Briefly speaking, SMP algorithms provide a decomposition of the geometry into its natural vibration modes. The resulting components, analogous to the Fourier Transform for 1D signals, are linked to intrinsic properties of the object, such as (a)symmetry, believed to be a crucial component of dysmorphology. The accuracy and precision of the algorithms used for geometric processing play a crucial role in the project given the interest in neuropsychiatric disorders, where craniofacial dysmorphology is considerably more subtle than, for example, in Down syndrome. More information available at: |
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The Face3D
consortium (www.face3d.ac.uk) aims to
provide tools to extract important and potentially useful quantitative
information on facial shape from three-dimensional images and to develop
statistical models for Ø the characterization of the biological processes which underlie schizophrenia Ø the quantitative assessment of the outcome of orthognathic surgery. The project is funded by the Wellcome Trust, integrated by the following partners: n
The
University of Glasgow n Royal College of Surgeons in Ireland n Dublin City University n Institute of Technology, Tralee n University of Limerick |
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