AR3WS

"Acquiring and Responding to the 3D World, Smartly"

Coordinatore	UNIVERSITY COLLEGE LONDON    more  Organization address address: GOWER STREET city: LONDON postcode: WC1E 6BT contact info Titolo: Mr. Nome: Machell Cognome: Giles Email: send email Telefono: +44 20 3108 3020 Fax: +44 20 7813 2849
Nazionalità Coordinatore	United Kingdom [UK]
Totale costo	100˙000 €
EC contributo	100˙000 €
Programma	FP7-PEOPLE Specific programme "People" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013)
Code Call	FP7-PEOPLE-2011-CIG
Funding Scheme	MC-CIG
Anno di inizio	2012
Periodo (anno-mese-giorno)	2012-11-01   -   2016-10-31

 Partecipanti

#	participant	country	role	EC contrib. [€]
1	UNIVERSITY COLLEGE LONDON  Organization address address: GOWER STREET city: LONDON postcode: WC1E 6BT contact info Titolo: Mr. Nome: Machell Cognome: Giles Email: send email Telefono: +44 20 3108 3020 Fax: +44 20 7813 2849	UK (LONDON)	coordinator	100˙000.00

Mappa

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 Obiettivo del progetto (Objective)

'Recent advances in sensors and imaging systems have greatly simplified scanning and acquisition both in terms of setup cost and acquisition times. As scanners and sensors become ubiquitous, efficient registration of multi-modal sensor inputs (e.g., images, 3D scans, depth scans), suitably representing them, and most importantly the ability to automatically reason and efficiently interact with the acquired data becomes crucial for enabling a smart world. We propose advances to all the stages of such a digital shape acquisition and analysis pipeline preparing us with tools necessary for appropriate use the stream of 3D content that is to follow in next years. More specifically, we propose to: (i) develop algorithms to efficiently combine photographs and 3D LiDAR scans for large scale acquisitions ranging from facades to city blocks, (ii) support analysis of the acquired scenes with man-made objects (e.g., mechanical parts and assemblies) to reveal underlying data decomposition and relations such as coplanarity, orthogonality, symmetry, regularity, etc., and (iii) use the extracted relations to support interactive navigation of the scenes for detecting damaged scene parts, plan building modifications and predicting possible functions of the individual segmented parts. The work will have direct applications in surveillance for assisted living, disaster management, emergency response, city planning, and also towards archival of historical data, digital restoration, and understanding of natural geometric growth processes.'