3D scan process optimisation study for rapid virtualization.

Angus P. Fitzpatrick; Paul K. Collins; Ian Gibson

doi:10.1016/j.procir.2020.02.248

3D scan process optimisation study for rapid virtualization.

Angus P. Fitzpatrick^*, Paul K. Collins, Ian Gibson

^*Corresponding author for this work

Design Engineering

Research output: Contribution to journal › Conference article › Academic › peer-review

Abstract

Introduction-Many of the problems facing 3d scanning as a digitisation method around the human form are caused by the time it takes to scan the entity. This can be solved by using multiple cameras organised in a way to scan the extremity simultaneously from multiple directions. This paper is the exploration around the minimum number of cameras needed to obtain a usable model. Methodology-Using a 5-stage experimental process for 17 subjects and batch processing each stage, determined the most efficient workflow. Results-Excluding the exploration subject, it was found that the use of 4 cameras simultaneously was 5.5 times faster, including processing time then it was to use a single camera. Conclusion-using multiple cameras makes the process 5.5 times faster, as well as batch processing, and having a standardised method to enable the use of algorithmic file processing.

Original language	English
Pages (from-to)	911-916
Number of pages	6
Journal	Procedia CIRP
Volume	91
DOIs	https://doi.org/10.1016/j.procir.2020.02.248
Publication status	Published - 2020
Event	30th CIRP Design on Design, CIRP Design 2020 - Pretoria, South Africa Duration: 5 May 2020 → 8 May 2020

Keywords

3D Scanning
Process Optimisation
Virtualization

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Fitzpatrick-2020-D-scan-process-optimisation-study-fFinal published version, 988 KBLicence: CC BY-NC-ND

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title = "3D scan process optimisation study for rapid virtualization.",

abstract = "Introduction-Many of the problems facing 3d scanning as a digitisation method around the human form are caused by the time it takes to scan the entity. This can be solved by using multiple cameras organised in a way to scan the extremity simultaneously from multiple directions. This paper is the exploration around the minimum number of cameras needed to obtain a usable model. Methodology-Using a 5-stage experimental process for 17 subjects and batch processing each stage, determined the most efficient workflow. Results-Excluding the exploration subject, it was found that the use of 4 cameras simultaneously was 5.5 times faster, including processing time then it was to use a single camera. Conclusion-using multiple cameras makes the process 5.5 times faster, as well as batch processing, and having a standardised method to enable the use of algorithmic file processing.",

keywords = "3D Scanning, Process Optimisation, Virtualization",

author = "Fitzpatrick, {Angus P.} and Collins, {Paul K.} and Ian Gibson",

year = "2020",

doi = "10.1016/j.procir.2020.02.248",

language = "English",

volume = "91",

pages = "911--916",

journal = "Procedia CIRP",

issn = "2212-8271",

publisher = "Elsevier",

note = "30th CIRP Design on Design, CIRP Design 2020 ; Conference date: 05-05-2020 Through 08-05-2020",

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TY - JOUR

T1 - 3D scan process optimisation study for rapid virtualization.

AU - Fitzpatrick, Angus P.

AU - Collins, Paul K.

AU - Gibson, Ian

PY - 2020

Y1 - 2020

N2 - Introduction-Many of the problems facing 3d scanning as a digitisation method around the human form are caused by the time it takes to scan the entity. This can be solved by using multiple cameras organised in a way to scan the extremity simultaneously from multiple directions. This paper is the exploration around the minimum number of cameras needed to obtain a usable model. Methodology-Using a 5-stage experimental process for 17 subjects and batch processing each stage, determined the most efficient workflow. Results-Excluding the exploration subject, it was found that the use of 4 cameras simultaneously was 5.5 times faster, including processing time then it was to use a single camera. Conclusion-using multiple cameras makes the process 5.5 times faster, as well as batch processing, and having a standardised method to enable the use of algorithmic file processing.

AB - Introduction-Many of the problems facing 3d scanning as a digitisation method around the human form are caused by the time it takes to scan the entity. This can be solved by using multiple cameras organised in a way to scan the extremity simultaneously from multiple directions. This paper is the exploration around the minimum number of cameras needed to obtain a usable model. Methodology-Using a 5-stage experimental process for 17 subjects and batch processing each stage, determined the most efficient workflow. Results-Excluding the exploration subject, it was found that the use of 4 cameras simultaneously was 5.5 times faster, including processing time then it was to use a single camera. Conclusion-using multiple cameras makes the process 5.5 times faster, as well as batch processing, and having a standardised method to enable the use of algorithmic file processing.

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KW - Process Optimisation

KW - Virtualization

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