DocumentCode
3420103
Title
Locating Anatomical Points on Foot from 3D Point Cloud Data
Author
Jianhui Zhao ; Goonetilleke, R.S.
Author_Institution
Comput. Sch., Wuhan Univ., Wuhan
fYear
2006
fDate
Nov. 29 2006-Dec. 1 2006
Firstpage
603
Lastpage
607
Abstract
Algorithms are proposed to automatically locate the foot anatomical points from scanned 3D point data based on a novel method that uses the pternion point for foot alignment, whereby variations in the different dimensions are minimized. The detected foot malleoli and arch point are used to classify the foot type. Based on the automatically detected anatomical points, 9 foot dimensions of 10 participants were determined and compared with manual measurements.
Keywords
biology computing; computational geometry; footwear; spatial variables measurement; 3D point cloud data; arch point; foot alignment; foot dimensions; foot malleoli; pternion point; Data acquisition; Foot; Footwear; Object detection; Particle measurements; Performance evaluation; Position measurement; Shape; Surface fitting; Three-dimensional displays;
fLanguage
English
Publisher
ieee
Conference_Titel
Artificial Reality and Telexistence--Workshops, 2006. ICAT '06. 16th International Conference on
Conference_Location
Hangzhou
Print_ISBN
0-7695-2754-X
Type
conf
DOI
10.1109/ICAT.2006.82
Filename
4089322
Link To Document