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Online 4d reconstruction using multi-images available under open access

Journal
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Date Issued
July 30, 2013
Author(s)
Johnson, P. S.  
Doulamis, A.  
Moura Santo, P.  
Hadjiprocopi, A.  
Fritsch, D.  
Doulamis, Nikolaos D.  
Makantasis, K.  
Stork, A.  
Ioannides, Marinos  
Klein, M.  
Balet, O.  
Fellner, D.  
Weinlinger, G.  
Protopapadakis, E.  
Julien, M.  
DOI
10.5194/isprsannals-II-5-W1-169-2013
Abstract
The advent of technology in digital cameras and their incorporation into virtually any smart mobile device has led to an explosion of the number of photographs taken every day. Today, the number of images stored online and available freely has reached unprecedented levels. It is estimated that in 2011, there were over 100 billion photographs stored in just one of the major social media sites. This number is growing exponentially. Moreover, advances in the fields of Photogrammetry and Computer Vision have led to significant breakthroughs such as the Structure from Motion algorithm which creates 3D models of objects using their twodimensional photographs. The existence of powerful and affordable computational machinery not only the reconstruction of complex structures but also entire cities. This paper illustrates an overview of our methodology for producing 3D models of Cultural Heritage structures such as monuments and artefacts from 2D data (pictures, video), available on Internet repositories, social media, Google Maps, Bing, etc. We also present new approaches to semantic enrichment of the end results and their subsequent export to Europeana, the European digital library, for integrated, interactive 3D visualisation within regular web browsers using WebGl and X3D. Our main goal is to enable historians, architects, archaeologists, urban planners and affiliated professionals to reconstruct views of historical structures from millions of images floating around the web and interact with them.
Subjects

3D Reconstruction

Augmentation

Computer Vision

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ONLINE 4D.pdf

Size

550.1 KB

Format

Adobe PDF

Checksum (MD5)

3939fa772d14f01688ab8db5cc844650

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