Online from: 1989
Subject Area: Mechanical & Materials Engineering
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|Title:||Initial validation of point cloud data from a 3D body scanner|
|Author(s):||Terry Lerch, (Department of Engineering and Technology, Central Michigan University, Mount Pleasant, Michigan, USA), Sean Anthony, (Department of Engineering and Technology, Central Michigan University, Mount Pleasant, Michigan, USA), Tanya Domina, (Department of Human Environmental Studies, Central Michigan University, Mount Pleasant, Michigan, USA)|
|Citation:||Terry Lerch, Sean Anthony, Tanya Domina, (2008) "Initial validation of point cloud data from a 3D body scanner", International Journal of Clothing Science and Technology, Vol. 20 Iss: 5, pp.271 - 280|
|Keywords:||Data collection, Data structures, Image scanners|
|Article type:||Research paper|
|DOI:||10.1108/09556220810898881 (Permanent URL)|
|Publisher:||Emerald Group Publishing Limited|
|Acknowledgements:||The authors are indebted to Barb Wilson and Marybeth Mey of Central Michigan Community Hospital of Mt Pleasant, MI, USA for providing the CT scans of the dress form. They also thank Dr Pat Kinnicutt of Central Michigan University for his assistance with the data analysis. This work was funded from NSF Grant No. BES-0420791.|
Purpose – The purpose of this paper is to validate the accuracy of point cloud data generated from a 3D body scanner.
Design/methodology/approach – A female dress form was scanned with an X-ray computed tomography (CT) system and a 3D body scanning system. The point cloud data from four axial slices of the body scan (BS) data were compared with the corresponding axial slices from the CT data. Length and cross-sectional area measurements of each slice were computed for each scanning technique.
Findings – The point cloud data from the body scanner were accurate to at least 2.0 percent when compared with the CT data. In many cases, the length and area measurements from the two types of scans varied by less than 1.0 percent.
Research limitations/implications – Only two length measurements and a cross-sectional area measurement were compared for each axial slice, resulting in a good first attempt of validation of the BS data. Additional methods of comparison should be employed for complete validation of the data. The dress form was scanned only once with each scanning device, so little can be said about the repeatability of the results.
Practical implications – Accuracy of the point cloud data from the 3D body scanner indicates that the main issues for the use of body scanners as anthropometric measurement tools are those of standardization, feature locations, and positioning of the subject.
Originality/value – Comparisons of point cloud data from a 3D body scanner with CT data had not previously been performed, and these results indicate that the point cloud data are accurate to at least 2.0 percent.
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