Analysis of human motion variation patterns using UMPCA
| Autor: | Yaser Zerehsaz, Jionghua Judy Jin, Hadi Ibrahim Masoud |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Adult
Male 0209 industrial biotechnology Computer science Movement 0206 medical engineering Video Recording Physical Therapy Sports Therapy and Rehabilitation Human Factors and Ergonomics 02 engineering and technology Variation (game tree) External Data Representation Motion capture Motion (physics) Pattern Recognition Automated Young Adult 020901 industrial engineering & automation Humans Computer vision Tensor Safety Risk Reliability and Quality Engineering (miscellaneous) Principal Component Analysis business.industry Pattern recognition Equipment Design Middle Aged Data structure 020601 biomedical engineering Multilinear principal component analysis Linear Models Female Joints Artificial intelligence business Automobiles Algorithms Test data |
| Zdroj: | Applied ergonomics. 59 |
| ISSN: | 1872-9126 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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