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Peer-to-peer visualization of very large 3D landscape and city models using MPEG-4

Romain Cavagna 1, 2, * Jérôme Royan 2 Patrick Gioia 2 Christian Bouville 3 Maha Abdallah 1 Eliya Buyukkaya 1
* Corresponding author
1 MALIRE - Machine Learning and Information Retrieval
LIP6 - Laboratoire d'Informatique de Paris 6
3 BUNRAKU - Perception, decision and action of real and virtual humans in virtual environments and impact on real environments
IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires, ENS Cachan - École normale supérieure - Cachan, Inria Rennes – Bretagne Atlantique
Abstract : The recent availability of broadband Internet access and web-based visualization techniques is paving the way for a large scale use of 3D landscape and city models in a great variety of professional and mass market services. To make such services appealing to a large audience, these 3D models must reach a sufficient level of realism and accuracy. Many solutions are now available to automatically generate 3D models of huge urban environments. Geographic Information System (GIS) databases (i.e. terrain elevation grids, orthophotographs, buildings footprint and height) provide a good basis for generating such models at affordable cost with minimum human intervention. However, the growing size of the generated representations will favor streaming over download-and-play. Moreover, the new market for virtual worlds is likely to be soon demanding in interoperability. The goal of this paper is to show how solutions based on hierarchical Level Of Details (LOD) models and view dependent progressive streaming can efficiently be implemented using the MPEG-4 AFX standard in peer-to-peer networks architectures, solving both streaming and interoperability issues.
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Submitted on : Saturday, May 1, 2010 - 4:48:47 PM
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Romain Cavagna, Jérôme Royan, Patrick Gioia, Christian Bouville, Maha Abdallah, et al.. Peer-to-peer visualization of very large 3D landscape and city models using MPEG-4. Signal Processing: Image Communication, Elsevier, 2009, Signal Processing: Image Communication, 24 (1-2), pp.115 - 121. ⟨10.1016/j.image.2008.10.012⟩. ⟨inria-00479661⟩



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