Paper Abstract and Keywords |
Presentation |
2022-09-13 14:00
Study on eye tracking based skill level estimation for assisting collaborative work Ryohei Saijo, Hiromu Miyashita, Shohei Matsuo (NTT) LOIS2022-11 IE2022-33 EMM2022-39 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
In collaborative work among multiple workers with different skill levels, communication discrepancies may occur due to differences in the skill level of the workers. Such discrepancies in communication lead to a deterioration in the efficiency and quality of work. This study aims to eliminate such discrepancies by presenting supplementary information to users during work according to their skill level. This paper first studied a method for estimating skill level based on collected gaze data during work on the Tsume-Shogi (Japanese chess) task performed in a VR space. The results suggest that it is possible to discriminate skilled from unskilled players using a model learned by SVM by extracting gaze data during the first 3 seconds of response to the task. It advanced the development of the skill level estimation method for assisting collaborative work. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
eye tracking / skill level estimation / assisting cooperative work / VR / tsume shougi(japanese chess) / mind-to-mind communications / / |
Reference Info. |
IEICE Tech. Rep., vol. 122, no. 177, LOIS2022-11, pp. 7-12, Sept. 2022. |
Paper # |
LOIS2022-11 |
Date of Issue |
2022-09-06 (LOIS, IE, EMM) |
ISSN |
Online edition: ISSN 2432-6380 |
Copyright and reproduction |
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LOIS2022-11 IE2022-33 EMM2022-39 |