کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4972190 | 1365394 | 2017 | 9 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Analysis of human motion variation patterns using UMPCA
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موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
تعامل انسان و کامپیوتر
پیش نمایش صفحه اول مقاله
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چکیده انگلیسی
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.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Applied Ergonomics - Volume 59, Part A, March 2017, Pages 401-409
Journal: Applied Ergonomics - Volume 59, Part A, March 2017, Pages 401-409
نویسندگان
Hadi Ibrahim Masoud, Yaser Zerehsaz, Jionghua (Judy) Jin,