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Furniture layout design aided system using subjective reward
Author(s): Tomohiro Matsuno; Yuji Hatanaka; Wataru Sunayama; Kazunori Ogohara
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Paper Abstract

Several studies for layout design optimization depend on evaluation indices with necessary passage, spaciousness, etc. It is difficult to obtain a friendly layout by using conventional methods. The layout design-aided model in this study is a residence space, and there are eight types of furniture. All furniture is first allocated to each room by using a genetic algorithm. All allocated furniture’s initial arrangements in each room are then determined by using Q-learning. A user checks the initial layout through virtual reality and evaluates it subjectively. The layout for a specific user is flexibly fixed by applying Q-learning, and a user subjective reward is added. As a result of observer experiments, more than half of the furniture can be arranged in an ideal position for a user, and a satisfactory layout is successfully generated.

Paper Details

Date Published: 22 March 2019
PDF: 6 pages
Proc. SPIE 11049, International Workshop on Advanced Image Technology (IWAIT) 2019, 110492X (22 March 2019); doi: 10.1117/12.2521524
Show Author Affiliations
Tomohiro Matsuno, Univ. of Shiga Prefecture (Japan)
Yuji Hatanaka, Univ. of Shiga Prefecture (Japan)
Wataru Sunayama, Univ. of Shiga Prefecture (Japan)
Kazunori Ogohara, Univ. of Shiga Prefecture (Japan)


Published in SPIE Proceedings Vol. 11049:
International Workshop on Advanced Image Technology (IWAIT) 2019
Qian Kemao; Kazuya Hayase; Phooi Yee Lau; Wen-Nung Lie; Yung-Lyul Lee; Sanun Srisuk; Lu Yu, Editor(s)

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