Morphological Analysis of 3D Faces for Weight Gain Assessment

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Show simple item record Giorgi, Daniela en_US Pascali, Maria Antonietta en_US Raccichini, Giovanni en_US Colantonio, Sara en_US Salvetti, Ovidio en_US
dc.contributor.editor I. Pratikakis and M. Spagnuolo and T. Theoharis and L. Van Gool and R. Veltkamp en_US 2015-04-27T11:03:36Z 2015-04-27T11:03:36Z 2015 en_US
dc.identifier.uri en_US
dc.description.abstract In this paper we analyse patterns in face shape variation due to weight gain. We propose the use of persistent homology descriptors to get geometric and topological information about the configuration of anthropometric 3D face landmarks. In this way, evaluating face changes boils down to comparing the descriptors computed on 3D face scans taken at different times. By applying dimensionality reduction techniques to the dissimilarity matrix of descriptors, we get a shape space in which each face is a point and face shape variations are encoded as trajectories in that space. Our first results show that persistent homology is able to identify features which are well-related to overweight, and may help assessing individual weight trends. The research is carried out in the context of the European project SEMEOTICONS, which is developing a multisensory platform which detects and monitors over time facial signs of cardio-metabolic risk. en_US
dc.publisher The Eurographics Association en_US
dc.subject Feature Measurement en_US
dc.subject Feature representation en_US
dc.subject Size and shape en_US
dc.title Morphological Analysis of 3D Faces for Weight Gain Assessment en_US
dc.description.seriesinformation Eurographics Workshop on 3D Object Retrieval en_US
dc.description.sectionheaders 3D Facial Analysis and Retrieval en_US
dc.identifier.doi 10.2312/3dor.20151055 en_US
dc.identifier.pages 55-62 en_US

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