PUMA
Istituto di Scienza e Tecnologie dell'Informazione     
Pintus R., Gobbetti E., Callieri M. A streaming framework for seamless detailed photo blending on massive point clouds. In: EG 2011 - Eurographics 2011: the 32nd annual conference of the European Association for Computer Graphics (Llandudno, UK, 11-15 aprile 2011). Proceedings, pp. 25 - 32. Visualization and Medical Graphics group at the School of Computer Science, Bangor University. (Eurographics Area Papers). EuroGraphics, 2011.
 
 
Abstract
(English)
We present an efficient scalable streaming technique for mapping highly detailed color information on extremely dense point clouds. Our method does not require meshing or extensive processing of the input model, works on a coarsely spatially-reordered point stream and can adaptively refine point cloud geometry on the basis of image content. Seamless multi-band image blending is obtained by using GPU accelerated screen-space operators, which solve point set visibility, compute a per-pixel view-dependent weight and ensure a smooth weighting function over each input image. The proposed approach works independently on each image in a memory coherent manner, and can be easily extended to include further image quality estimators. The effectiveness of the method is demonstrated on a series of massive real-world point datasets.
URL: http://www.crs4.it/vic/cgi-bin/bib-page.cgi?id=%27Pintus:2011:SFD%27
Subject 3D models
Color mapping
Huge dataset
Out of core
I.3.7 Three-Dimensional Graphics and Realism
65D18 Computer graphics, image analysis, and computational geometry


Icona documento 1) Download Document PDF


Icona documento Open access Icona documento Restricted Icona documento Private

 


Per ulteriori informazioni, contattare: Librarian http://puma.isti.cnr.it

Valid HTML 4.0 Transitional