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Título: | Integrating human body mocaps into Blender using RGB images |
Autor: | Sánchez-Riera, Jordi CSIC ORCID ; Moreno-Noguer, Francesc CSIC ORCID | Palabras clave: | MoCap 2D 3D human pose estimation Synthetic human model Action mimic |
Fecha de publicación: | 2020 | Editor: | IARIA (Association) | Citación: | International Conference on Advances in Computer-Human Interactions (ACHI): 285-290 (2020) | Resumen: | Reducing the complexity and cost of a Motion Capture (MoCap) system has been of great interest in recent years. Unlike other systems that use depth range cameras, we present an algorithm that is capable of working as a MoCap system with a single Red-Green-Blue (RGB) camera, and it is completely integrated in an off-the-shelf rendering software. This makes our system easily deployable in outdoor and unconstrained scenarios. Our approach builds upon three main modules. First, given solely one input RGB image, we estimate 2D body pose; the second module estimates the 3D human pose from the previously calculated 2D coordinates, and the last module calculates the necessary rotations of the joints given the goal 3D point coordinates and the 3D virtual human model. We quantitatively evaluate the first two modules using synthetic images, and provide qualitative results of the overall system with real images recorded from a webcam. | Descripción: | Trabajo presentado en el 13th International Conference on Advances in Computer-Human Interactions, celebrado en Valencia (España), del 21 al 25 de noviembre de 2020 | Versión del editor: | https://www.iaria.org/conferences2020/ACHI20.html | URI: | http://hdl.handle.net/10261/235595 | Identificadores: | issn: 2308-4138 isbn: 978-1-61208-761-0 |
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2359-Integrating-Human-Body-MoCaps-into-Blender-using-RGB-Images.pdf | 2,71 MB | Adobe PDF | Visualizar/Abrir |
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