title: Analysis of human motion variation patterns using UMPCA.
abstract: The rapid development of motion capture technologies has greatly increased the use of human motion data in many applications. This has increased the demand to have an effective means to systematically analyze those massive data in order to understand human motion variation patterns. This paper studies one typical type of motion data, which are recorded as multi-stream trajectories of human joints. Such a high dimensional multi-stream data structure makes it difficult to directly perform visual comparisons or simply apply conventional methods such as PCA to capture the variation of human motion patterns. In this paper, a high order array (tensor) is suggested for data representation, based on which the Uncorrelated Multilinear Principal Component Analysis (UMPCA) is applied to analyze the variation of human motion patterns. A simulation study is presented to show the superiority of UMPCA over PCA in preserving the cross-correlation among multi-stream trajectories. The effectiveness of UMPCA is also demonstrated using a case study for analyzing vehicle ingress test data.
authors.affiliation: Department of Industrial Engineering, University of Jeddah, Jeddah, Saudi Arabia. Electronic address: masoud@uj.edu.sa.
authors.forename: Hadi Ibrahim
authors.initials: HI
authors.lastname: Masoud
authors.affiliation: Industrial and Operations Engineering, University of Michigan, Ann Arbor, USA. Electronic address: yzereh@umich.edu.
authors.forename: Yaser
authors.initials: Y
authors.lastname: Zerehsaz
authors.affiliation: Industrial and Operations Engineering, University of Michigan, Ann Arbor, USA. Electronic address: jhjin@umich.edu.
authors.forename: Jionghua Judy
authors.initials: JJ
authors.lastname: Jin
mesh_terms: D000328:Adult; D000465:Algorithms; D001336:Automobiles; D004867:Equipment Design; D005260:Female; D006801:Humans; D007596:Joints / Q000502:physiology*; D016014:Linear Models; D008297:Male; D008875:Middle Aged; D009068:Movement / Q000502:physiology*; D010363:Pattern Recognition, Automated; D025341:Principal Component Analysis / Q000379:methods*; D014741:Video Recording / Q000379:methods; D055815:Young Adult
keywords: Human motion; UMPCA; Variation analysis