Title :
Locating Anatomical Points on Foot from 3D Point Cloud Data
Author :
Jianhui Zhao ; Goonetilleke, R.S.
Author_Institution :
Comput. Sch., Wuhan Univ., Wuhan
fDate :
Nov. 29 2006-Dec. 1 2006
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;
Conference_Titel :
Artificial Reality and Telexistence--Workshops, 2006. ICAT '06. 16th International Conference on
Conference_Location :
Hangzhou
Print_ISBN :
0-7695-2754-X
DOI :
10.1109/ICAT.2006.82