| IEICE Technical Committee Submission System Conference Paper's Information |
Online Proceedings [Sign in] Tech. Rep. Archives |
| Go Top Page | Go Previous | [Japanese] / [English] |
| Paper Abstract and Keywords | ||
| Presentation | 2021-10-22 13:10 A scanpath prediction model using deep learning considering the context of the gazing objects Yuhei Ohsawa, Takeshi Kohama (Kindai Univ.)  HIP2021-43 |
|
| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Since the human gaze is a biological signal which reflects internal states such as consciousness and attention, it is possible to develop technology for estimating human psychology by a gaze predicting system. In this study, we built a deep learning model that can reproduce human eye movement based on a constructive approach. First, we verified whether the encoder part of a typical image classification model could extract features that determine human eye movements from image statistics using a previous learning model. Next, we developed a deep learning model with a Seq2Seq structure that combines the encoder part of a typical image classification model with an RNN mechanism to construct a time series generation model with the context among objects and reproduced eye movements for still images. In order to evaluate the model performance, we calculated the cross-correlation coefficient between cumulative eye gaze distributions generated from the actual eye movements and the model outputs, and the average value for all validation data was 0.459. Since a small but positive correlation was found and temporal eye transitions were observed for objects and features that are likely to attract attention in the image, the proposed model can at least link image statistics with temporal characteristics of eye movements. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Visual system / Deep learning model / Gaze prediction / Scanpath / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 121, no. 211, HIP2021-43, pp. 69-74, Oct. 2021. | |
| Paper # | HIP2021-43 | |
| Date of Issue | 2021-10-14 (HIP) | |
| ISSN | Online edition: ISSN 2432-6380 | |
| Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) | |
| Download PDF | HIP2021-43 |
|
| Conference Information | |
| Committee | HIP |
| Conference Date | 2021-10-21 - 2021-10-22 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Paper Information | |
| Registration To | HIP |
| Conference Code | 2021-10-HIP |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | A scanpath prediction model using deep learning considering the context of the gazing objects |
| Sub Title (in English) | |
| Keyword(1) | Visual system |
| Keyword(2) | Deep learning model |
| Keyword(3) | Gaze prediction |
| Keyword(4) | Scanpath |
| Keyword(5) | |
| Keyword(6) | |
| Keyword(7) | |
| Keyword(8) | |
| 1st Author's Name | Yuhei Ohsawa |
| 1st Author's Affiliation | Kindai University (Kindai Univ.) |
| 2nd Author's Name | Takeshi Kohama |
| 2nd Author's Affiliation | Kindai University (Kindai Univ.) |
| 3rd Author's Name | |
| 3rd Author's Affiliation | () |
| 4th Author's Name | |
| 4th Author's Affiliation | () |
| 5th Author's Name | |
| 5th Author's Affiliation | () |
| 6th Author's Name | |
| 6th Author's Affiliation | () |
| 7th Author's Name | |
| 7th Author's Affiliation | () |
| 8th Author's Name | |
| 8th Author's Affiliation | () |
| 9th Author's Name | |
| 9th Author's Affiliation | () |
| 10th Author's Name | |
| 10th Author's Affiliation | () |
| 11th Author's Name | |
| 11th Author's Affiliation | () |
| 12th Author's Name | |
| 12th Author's Affiliation | () |
| 13th Author's Name | |
| 13th Author's Affiliation | () |
| 14th Author's Name | |
| 14th Author's Affiliation | () |
| 15th Author's Name | |
| 15th Author's Affiliation | () |
| 16th Author's Name | |
| 16th Author's Affiliation | () |
| 17th Author's Name | |
| 17th Author's Affiliation | () |
| 18th Author's Name | |
| 18th Author's Affiliation | () |
| Speaker | Author-1 |
| Date Time | 2021-10-22 13:10:00 |
| Presentation Time | 25 minutes |
| Registration for | HIP |
| Paper # | HIP2021-43 |
| Volume (vol) | vol.121 |
| Number (no) | no.211 |
| Page | pp.69-74 |
| #Pages | 6 |
| Date of Issue | 2021-10-14 (HIP) |
[Return to Top Page]