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Visualization and Classification of Strategy for Entering Car
Technical Paper
2005-01-2683
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
This paper proposes a method for visualizing and classifying the variation in the motions of a person when entering a passenger vehicle. Entering behaviors vary greatly between individuals, especially if the vehicle door is designed to have large clearance. The present study was conducted with the aim of supporting the design process of seats and front doors by visualizing possible variations of entering motions using a motion database, rather than calculating a single representative movement. The motion database is consist of different motions caused by various seats, and the motions are classified by mapping them into two-dimensional plane according to the similarities between them. A representative entering motion for a clustered motion strategy group is synthesized and visualized on the 2D distribution plane by interpolating existing motions in the database.
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Authors
- Katsuaki Kawachi - Digital Human Research Center, AIST (The National Institute of Advanced Industrial Science and Technology), Japan
- Kei Aoki - Digital Human Research Center, AIST (The National Institute of Advanced Industrial Science and Technology), Japan
- Masaaki Mochimaru - Digital Human Research Center, AIST (The National Institute of Advanced Industrial Science and Technology), Japan
- Makiko Kouchi - Digital Human Research Center, AIST (The National Institute of Advanced Industrial Science and Technology), Japan
Citation
Kawachi, K., Aoki, K., Mochimaru, M., and Kouchi, M., "Visualization and Classification of Strategy for Entering Car," SAE Technical Paper 2005-01-2683, 2005, https://doi.org/10.4271/2005-01-2683.Also In
References
- Lawrence Neil D. Gaussian process models for visualisation of high dimensional data Saul L. Thrun S. Schőlkopf, B. Advances in Neural Information Processing Systems MIT Press Cambridge, MA 2004
- Kawachi, Katsuaki Kanade, Takeo Suzuki Hiromasa A lightweight algorithm for real-time motion synthesis Proceedings of the ACM Symposium on Virtual Reality Software and Technology 49 56 November 2004