TY - GEN
T1 - Dynamic 3d mesh reconstruction based on nonrigid iterative closest-farthest points registration
AU - Tajdari, Farzam
AU - Kwa, Felix
AU - Versteegh, Christiaan
AU - Huysmans, Toon
AU - Song, Yu
PY - 2022
Y1 - 2022
N2 - Fitting apparel and apparel in performing different activities is essential for the functional yet comfortable experience of the user. 4D scans, i.e. 3D scans in continuous timestamps, of the body (part) in performing those activities are the basis for the design of garments/apparel in 4D. In this paper, we proposed a semi-automatic workflow for constructing 4D scans of the body parts with the emphasis on registering noisy scans at a given timestamp. Continuous 3D scans regarding the moving body parts are captured first from different depth cameras from different view angles. In a given timestamp, the collected 3D scans are roughly aligned to a template using the rigid Iterative Closest Points (ICP) algorithm. Then these scans are further registered using a newly proposed non-rigid Iterative Closest-Farthest Points (ICFP) algorithm, in which correspondences between the source and the target are established by either closest or farthest points based on the newly defined logical distance concept and the probability theory. Experimental results indicated that the ICFP method is robust against noise and the scanning accuracy can be as high as 3.4 %. It also reveals that, for the human foot, the differences of ball width and ball angles between the loaded and the unloaded situation can be as large as 8 mm and 2 degrees, respectively. This highlights the importance of using 4D scan in designing garments and apparel.
AB - Fitting apparel and apparel in performing different activities is essential for the functional yet comfortable experience of the user. 4D scans, i.e. 3D scans in continuous timestamps, of the body (part) in performing those activities are the basis for the design of garments/apparel in 4D. In this paper, we proposed a semi-automatic workflow for constructing 4D scans of the body parts with the emphasis on registering noisy scans at a given timestamp. Continuous 3D scans regarding the moving body parts are captured first from different depth cameras from different view angles. In a given timestamp, the collected 3D scans are roughly aligned to a template using the rigid Iterative Closest Points (ICP) algorithm. Then these scans are further registered using a newly proposed non-rigid Iterative Closest-Farthest Points (ICFP) algorithm, in which correspondences between the source and the target are established by either closest or farthest points based on the newly defined logical distance concept and the probability theory. Experimental results indicated that the ICFP method is robust against noise and the scanning accuracy can be as high as 3.4 %. It also reveals that, for the human foot, the differences of ball width and ball angles between the loaded and the unloaded situation can be as large as 8 mm and 2 degrees, respectively. This highlights the importance of using 4D scan in designing garments and apparel.
KW - 4D scans
KW - accuracy
KW - logical distance
KW - non-rigid Iterative Closest-Farthest Points (ICFP)
KW - robust
UR - http://www.scopus.com/inward/record.url?scp=85142521808&partnerID=8YFLogxK
U2 - 10.1115/DETC2022-90073
DO - 10.1115/DETC2022-90073
M3 - Conference contribution
AN - SCOPUS:85142521808
T3 - Proceedings of the ASME Design Engineering Technical Conference
BT - 42nd Computers and Information in Engineering Conference (CIE)
PB - The American Society of Mechanical Engineers (ASME)
T2 - ASME 2022 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC-CIE 2022
Y2 - 14 August 2022 through 17 August 2022
ER -