Difference between revisions of "About"
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| − | <b>Project SHARED</b> is a French National project funded by ANR(L'Agence Nationale de la Recherche) in the framework of "Chaires d'Excellence" program. SHARED seeks to investigate novel shape analysis methods that exploit large redundancy of information from dynamic or movement data.<br /><br /> | + | <b>Project SHARED</b> is a French National project funded by ANR(L'Agence Nationale de la Recherche) in the framework of "Chaires d'Excellence" program. |
| + | * Period: 15 Dec 2010 ~ 14 Dec 2014 | ||
| + | * Budget: 220 000 Euros | ||
| + | |||
| + | SHARED seeks to investigate novel shape analysis methods that exploit large redundancy of information from dynamic or movement data.<br /><br /> | ||
<!-- *First, a large enough collection of dynamic, time-varying data sets should be acquired. Appreciably, with the recent advances in imaging technologies we now have growing accessibility to capture shape and motion of people with high frequency. For example, we track the location of selected skin surfaces (markers) using a number of synchronized cameras. After post-processing of marker trajectories we obtain sequences of human body motions in the form of animated meshes. | <!-- *First, a large enough collection of dynamic, time-varying data sets should be acquired. Appreciably, with the recent advances in imaging technologies we now have growing accessibility to capture shape and motion of people with high frequency. For example, we track the location of selected skin surfaces (markers) using a number of synchronized cameras. After post-processing of marker trajectories we obtain sequences of human body motions in the form of animated meshes. | ||
Revision as of 16:27, 21 December 2012
Project SHARED - Shape Analysis and Registration of People Using Dynamic Data
Project SHARED is a French National project funded by ANR(L'Agence Nationale de la Recherche) in the framework of "Chaires d'Excellence" program.
- Period: 15 Dec 2010 ~ 14 Dec 2014
- Budget: 220 000 Euros
SHARED seeks to investigate novel shape analysis methods that exploit large redundancy of information from dynamic or movement data.
The SHARED objectives could be briefly described as follows:
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