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A Study into Autonomous Scanning for 3D Model Construction

O’Hare, D, Hurst, W, Tully, D and El Rhalibi, A (2017) A Study into Autonomous Scanning for 3D Model Construction. In: Springer Lecture Notes in Computer Science (LNCS) series. . pp. 182-190. (The International Conference on E-learning and Games (Edutainment 2017), 26 June 2017 - 28 June 2017, Bournemouth, UK).

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3D scanning and printing has the potential to revolutionise the world. It offers a bridge between the virtual environment and the tangible world. The use of 3D scanners to capture and recreate defining objects is known as 3D virtualisation. It involves capturing a real-life scene using laser technology and representing its geometry using 3D modelling software or 3D printers. Despite being a relatively young technology, 3D printing has now become accessible and a part of modern industry. The printing of a 3D generated model can change the way in which an individual understands a concept, environment or communicates an idea. This has multiple benefits, for education, skills development, training and within the construction industry. However, using this technology relies on the operator having the skills and training required to generate accurate 3D models, and account for errors in the mesh after scanning. As such, this paper details the development into an automated 3D scanning system, and a cloud-based printing platform, where models are intelligently printed by multiple devices. Its development allows the readiness of 3D printing capabilities to unskilled users, who have no education or training in 3D model construction. Objects can be instantly manipulated and transferred into free-to-use open source graphic software. The access to detailed 3D model construction has never been so accessible to the untrained.

Item Type: Conference or Workshop Item (Paper)
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
T Technology > T Technology (General)
Divisions: Computer Science & Mathematics
Publisher: Springer Verlag, LNCS
Date Deposited: 03 May 2017 09:17
Last Modified: 13 Apr 2022 15:15
URI: https://researchonline.ljmu.ac.uk/id/eprint/6336
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