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Título: | Single view facial hair 3D reconstruction |
Autor: | Rotger, Gemma; Moreno-Noguer, Francesc CSIC ORCID ; Lumbreras, Felipe; Agudo, Antonio CSIC ORCID | Palabras clave: | 3D vision Shape Reconstruction Facial Hair Modeling |
Fecha de publicación: | 1-jul-2019 | Editor: | Springer Nature | Citación: | Pattern Recognition and Image Analysis: 423-436 (2019) | Resumen: | In this work, we introduce a novel energy-based framework that addresses the challenging problem of 3D reconstruction of facial hair from a single RGB image. To this end, we identify hair pixels over the image via texture analysis and then determine individual hair fibers that are modeled by means of a parametric hair model based on 3D helixes. We propose to minimize an energy composed of several terms, in order to adapt the hair parameters that better fit the image detections. The final hairs respond to the resulting fibers after a post-processing step where we encourage further realism. The resulting approach generates realistic facial hair fibers from solely an RGB image without assuming any training data nor user interaction. We provide an experimental evaluation on real-world pictures where several facial hair styles and image conditions are observed, showing consistent results and establishing a comparison with respect to competing approaches. | Descripción: | Trabajo presentado en el Iberian Conference on Pattern Recognition and Image Analysis, celebrado en Madrid (España), del 1 al 4 de julio de 2019 | Versión del editor: | http://dx.doi.org/10.1007/978-3-030-31332-6_37 | URI: | http://hdl.handle.net/10261/207510 | DOI: | 10.1007/978-3-030-31332-6_37 | Identificadores: | doi: 10.1007/978-3-030-31332-6_37 issn: 0302-9743 isbn: 978-3-030-31332-6 |
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2189-Single-View-Facial-Hair-3D-Reconstruction.pdf | 9,55 MB | Adobe PDF | Visualizar/Abrir |
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