| Paper Abstract and Keywords |
| Presentation |
2021-03-04 13:50
A method of Generating Color Palettes with Deep Neural Networks Considering Human Perception and Its Evaluation Beiying Liu, Kaoru Arakawa (Meiji Univ.) SIS2020-46 |
| Abstract |
(in Japanese) |
(See Japanese page) |
| (in English) |
A method for generating color palettes from images is proposed and the obtained color palettes are evaluated both objectively and subjectively compared with conventional methods. The proposed methods utilizes deep neural networks (DNN) in order to consider human perception to the images. Two aspects of human perception are considered; one is attention and the other is preference to colors. Two deep neural-net systems are adopted here for each. The former is trained with target images obtained by an eye tracker, and the latter is trained with database of color selection by human. S and H components in the obtained color palettes are analyzed and also subjective test was performed by questionnaire to evaluate performance of the proposed method compared with conventional ones. It is shown that the proposed system is effective for realizing color palettes which reflect human perception to color images. |
| Keyword |
(in Japanese) |
(See Japanese page) |
| (in English) |
color / perception / color palette / deep learning / gaze tracking / / / |
| Reference Info. |
IEICE Tech. Rep., vol. 120, no. 415, SIS2020-46, pp. 61-66, March 2021. |
| Paper # |
SIS2020-46 |
| Date of Issue |
2021-02-25 (SIS) |
| 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 |
SIS2020-46 |
| Conference Information |
| Committee |
SIS |
| Conference Date |
2021-03-04 - 2021-03-05 |
| Place (in Japanese) |
(See Japanese page) |
| Place (in English) |
Online |
| Topics (in Japanese) |
(See Japanese page) |
| Topics (in English) |
Soft Computing, etc. |
| Paper Information |
| Registration To |
SIS |
| Conference Code |
2021-03-SIS |
| Language |
English (Japanese title is available) |
| Title (in Japanese) |
(See Japanese page) |
| Sub Title (in Japanese) |
(See Japanese page) |
| Title (in English) |
A method of Generating Color Palettes with Deep Neural Networks Considering Human Perception and Its Evaluation |
| Sub Title (in English) |
|
| Keyword(1) |
color |
| Keyword(2) |
perception |
| Keyword(3) |
color palette |
| Keyword(4) |
deep learning |
| Keyword(5) |
gaze tracking |
| Keyword(6) |
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| Keyword(7) |
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| Keyword(8) |
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| 1st Author's Name |
Beiying Liu |
| 1st Author's Affiliation |
Meiji University (Meiji Univ.) |
| 2nd Author's Name |
Kaoru Arakawa |
| 2nd Author's Affiliation |
Meiji University (Meiji Univ.) |
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| Speaker |
Author-1 |
| Date Time |
2021-03-04 13:50:00 |
| Presentation Time |
20 minutes |
| Registration for |
SIS |
| Paper # |
SIS2020-46 |
| Volume (vol) |
vol.120 |
| Number (no) |
no.415 |
| Page |
pp.61-66 |
| #Pages |
6 |
| Date of Issue |
2021-02-25 (SIS) |