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Age‐related gait motion transformation based on biomechanical observations
Author(s) -
Jung Sunjin,
Hong Seokpyo,
Cho Kyungmin,
Eom Haegwang,
Choi Byungkuk,
Noh Junyong
Publication year - 2017
Publication title -
computer animation and virtual worlds
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.225
H-Index - 49
eISSN - 1546-427X
pISSN - 1546-4261
DOI - 10.1002/cav.1774
Subject(s) - computer science , gait , kinematics , motion (physics) , computer vision , artificial intelligence , focus (optics) , transformation (genetics) , ground reaction force , range (aeronautics) , gait cycle , motion capture , physical medicine and rehabilitation , physics , medicine , biology , classical mechanics , optics , biochemistry , materials science , composite material , gene
We present a novel approach for synthesizing human gait motions according to a range of input ages by transforming a given motion based on biomechanical observations. Given an original motion, our method first extracts gait cycles that are periodically defined by foot contact on the ground and then transforms the original motion to achieve a desirable posture and motions that respectively correspond to the input age. Among many biomechanical features that gradually change with aging, we mainly focus on spatiotemporal and kinematic features as well as postural changes. Exploiting these features, we formulate the biomechanical changes as continuous functions that reflect visually significant features corresponding to the input age. Finally, we demonstrate that our system can automatically generate plausible gait motions given a wide range of input ages.