Harvesting Dynamic 3D Worlds from Commodity Sensor Clouds

Tamy Boubekeur, Paolo Cignoni, Elmar Eisemann, Michael Goesele, Reinhard Klein, Stefan Roth, Michael Weinmann, and Michael Wimmer
In proceedings of Eurographics Workshop on Graphics and Cultural Heritage, The Eurographics Association, 2016
 

Abstract

The EU FP7 FET-Open project ”Harvest4D: Harvesting Dynamic 3D Worlds from Commodity Sensor Clouds” deals with the acquisition, processing, and display of dynamic 3D data. Technological progress is offering us a wide-spread availability of sensing devices that deliver different data streams, which can be easily deployed in the real world and produce streams of sampled data with increased density and easier iteration of the sampling process. These data need to be processed and displayed in a new way. The Harvest4D project proposes a radical change in acquisition and processing technology: instead of a goaldriven acquisition that determines the devices and sensors, its methods let the sensors and resulting available data determine the acquisition process. A variety of challenging problems need to be solved: huge data amounts, different modalities, varying scales, dynamic, noisy and colorful data. This short contribution presents a selection of the many scientific results produced by Harvest4D. We will focus on those results that could bring a major impact to the Cultural Heritage domain, namely facilitating the acquisition of the sampled data or providing advanced visual analysis capabilities.

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Bibtex

@INPROCEEDINGS{harvest4d_2016,
     author = {Boubekeur, Tamy and Cignoni, Paolo and Eisemann, Elmar and Goesele, Michael and Klein, Reinhard and
               Roth, Stefan and Weinmann, Michael and Wimmer, Michael},
      title = {Harvesting Dynamic 3D Worlds from Commodity Sensor Clouds},
  booktitle = {Eurographics Workshop on Graphics and Cultural Heritage},
       year = {2016},
  publisher = {The Eurographics Association},
   abstract = {The EU FP7 FET-Open project ''Harvest4D: Harvesting Dynamic 3D Worlds from Commodity Sensor Clouds''
               deals with the acquisition, processing, and display of dynamic 3D data. Technological progress is
               offering us a wide-spread availability of sensing devices that deliver different data streams, which
               can be easily deployed in the real world and produce streams of sampled data with increased density
               and easier iteration of the sampling process. These data need to be processed and displayed in a new
               way. The Harvest4D project proposes a radical change in acquisition and processing technology:
               instead of a goaldriven acquisition that determines the devices and sensors, its methods let the
               sensors and resulting available data determine the acquisition process. A variety of challenging
               problems need to be solved: huge data amounts, different modalities, varying scales, dynamic, noisy
               and colorful data. This short contribution presents a selection of the many scientific results
               produced by Harvest4D. We will focus on those results that could bring a major impact to the
               Cultural Heritage domain, namely facilitating the acquisition of the sampled data or providing
               advanced visual analysis capabilities.},
       issn = {2312-6124},
       isbn = {978-3-03868-011-6},
        url = {https://diglib.eg.org/handle/10.2312/gch20161378},
        doi = {10.2312/gch.20161378}
}