Extracting surface area coverage by superimposing 3D scan data

Peng Li; Brian D. Corner; Steven Paquette

doi:10.1117/12.341051

8 March 1999 Extracting surface area coverage by superimposing 3D scan data

Peng Li, Brian D. Corner, Steven Paquette

Proceedings Volume 3640, Three-Dimensional Image Capture and Applications II; (1999) https://doi.org/10.1117/12.341051
Event: Electronic Imaging '99, 1999, San Jose, CA, United States

Abstract

Surface area coverage is an important feature for evaluating the functionality of personal protective equipment and clothing. This paper present an approach for calculating surface area coverage of protective clothing by superimposing two 3D whole body scan images: a scan of a 'nude' human/mankind body and a scan of a clothed body. The basic approach is to align two scans and calculate the per vertex distance field between the two scanned surfaces. Because the clothed body has an extra surface layer relative to the nude scan, the distance field may be used to define covered or uncovered regions by setting a distance threshold based on the thickness of the clothing or equipment. This paper discusses the procedures required for estimating surface area coverage including data slicing, sorting, mesh generation and the computation of the distance field. Although the above method is straightforward to describe, some difficulties related to human body scanning had to be overcome in the practical application of the method. Some of these challenges included: 1) registration of two scan data sets with different shapes, 2) the frequency occurrence of void data, especially in the clothing scan; and 3) the clothing/equipment may cause tissue compression and deformation. This paper discusses these problems and our current solutions.

Citation Download Citation

Peng Li, Brian D. Corner, and Steven Paquette "Extracting surface area coverage by superimposing 3D scan data", Proc. SPIE 3640, Three-Dimensional Image Capture and Applications II, (8 March 1999); https://doi.org/10.1117/12.341051

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available