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Motion capture based on RGBD data from multiple sensors for avatar animation
dc.contributor | Pelechano Gómez, Núria |
dc.contributor.author | Vico Moya, Miguel Ángel |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament de Ciències de la Computació |
dc.date.accessioned | 2017-05-08T10:22:54Z |
dc.date.available | 2017-05-08T10:22:54Z |
dc.date.issued | 2016 |
dc.identifier.uri | http://hdl.handle.net/2117/104169 |
dc.description.abstract | With recent advances in technology and emergence of affordable RGB-D sensors for a wider range of users, markerless motion capture has become an active field of research both in computer vision and computer graphics. In this thesis, we designed a POC (Proof of Concept) for a new tool that enables us to perform motion capture by using a variable number of commodity RGB-D sensors of different brands and technical specifications on constraint-less layout environments. The main goal of this work is to provide a tool with motion capture capabilities by using a handful of RGB-D sensors, without imposing strong requirements in terms of lighting, background or extension of the motion capture area. Of course, the number of RGB-D sensors needed is inversely proportional to their resolution, and directly proportional to the size of the area to track to. Built on top of the OpenNI 2 library, we made this POC compatible with most of the nonhigh-end RGB-D sensors currently available in the market. Due to the lack of resources on a single computer, in order to support more than a couple of sensors working simultaneously, we need a setup composed of multiple computers. In order to keep data coherency and synchronization across sensors and computers, our tool makes use of a semi-automatic calibration method and a message-oriented network protocol. From color and depth data given by a sensor, we can also obtain a 3D pointcloud representation of the environment. By combining pointclouds from multiple sensors, we can collect a complete and animated 3D pointcloud that can be visualized from any viewpoint. Given a 3D avatar model and its corresponding attached skeleton, we can use an iterative optimization method (e.g. Simplex) to find a fit between each pointcloud frame and a skeleton configuration, resulting in 3D avatar animation when using such skeleton configurations as key frames. |
dc.language.iso | eng |
dc.publisher | Universitat Politècnica de Catalunya |
dc.subject | Àrees temàtiques de la UPC::Informàtica |
dc.subject.lcsh | Three-dimensional display systems |
dc.subject.lcsh | Human-computer interaction |
dc.subject.other | multi |
dc.subject.other | kinect |
dc.subject.other | 3D |
dc.subject.other | capture |
dc.subject.other | mocap |
dc.subject.other | master |
dc.subject.other | thesis |
dc.subject.other | fib |
dc.subject.other | upc |
dc.title | Motion capture based on RGBD data from multiple sensors for avatar animation |
dc.type | Master thesis |
dc.subject.lemac | Visualització tridimensional (Informàtica) |
dc.subject.lemac | Interacció persona-ordinador |
dc.identifier.slug | 108220 |
dc.rights.access | Open Access |
dc.date.updated | 2016-07-06T06:27:23Z |
dc.audience.educationlevel | Màster |
dc.audience.mediator | Facultat d'Informàtica de Barcelona |
dc.audience.degree | MÀSTER UNIVERSITARI EN INNOVACIÓ I RECERCA EN INFORMÀTICA (Pla 2012) |