| Paper Abstract and Keywords |
| Presentation |
2022-02-21 15:05
A Note on Personalized Saliency Prediction Based on User Similarity Considering Object Information in Images
Yuya Moroto, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) |
| Abstract |
(in Japanese) |
(See Japanese page) |
| (in English) |
This paper presents a personalized saliency map (PSM) prediction method using a small amount of gaze data based on user similarities considering object information in the image. The proposed methods uses the similarity between the gaze tendency of the target user and a group of users for which a large amount of gaze data has been obtained for training (training user group) to achieve highly accurate PSM prediction of the target user even if the amount of gaze data obtained from the target user is small. Specifically, a deep learning-based model is constructed for predicting the PSM of a training user group. Next, the similarity of the gazing tendency is calculated by using the PSM for the images that the training users and the target user commonly gaze at (training images). Since it has been reported that the human visual attention is related to objects, the proposed method calculates the similarity of gazing tendency between users based on the visual semantic information by considering the object information in the images. Finally, by using the PSM calculated by the deep learning-based model and the similarity of gazing tendency, our method can achieve highly accurate PSM prediction. At the end of this paper, we demonstrate the effectiveness of the proposed method by predicting the PSM of the target user in an experiment. |
| Keyword |
(in Japanese) |
(See Japanese page) |
| (in English) |
Saliency prediction / learning from small amount of data / object detection / saliecny map / deep learning / / / |
| Reference Info. |
ITE Tech. Rep., vol. 46, no. 6, ME2022-51, pp. 181-186, Feb. 2022. |
| Paper # |
ME2022-51 |
| Date of Issue |
2022-02-14 (MMS, ME, AIT) |
| ISSN |
Print edition: ISSN 1342-6893 Online edition: ISSN 2424-1970 |
| Download PDF |
|
| Conference Information |
| Committee |
AIT ME MMS IEICE-IE IEICE-ITS |
| Conference Date |
2022-02-21 - 2022-02-22 |
| Place (in Japanese) |
(See Japanese page) |
| Place (in English) |
online |
| Topics (in Japanese) |
(See Japanese page) |
| Topics (in English) |
|
| Paper Information |
| Registration To |
ME |
| Conference Code |
2022-02-AIT-ME-MMS-IE-ITS |
| Language |
Japanese |
| Title (in Japanese) |
(See Japanese page) |
| Sub Title (in Japanese) |
(See Japanese page) |
| Title (in English) |
A Note on Personalized Saliency Prediction Based on User Similarity Considering Object Information in Images |
| Sub Title (in English) |
|
| Keyword(1) |
Saliency prediction |
| Keyword(2) |
learning from small amount of data |
| Keyword(3) |
object detection |
| Keyword(4) |
saliecny map |
| Keyword(5) |
deep learning |
| Keyword(6) |
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| Keyword(7) |
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| 1st Author's Name |
Yuya Moroto |
| 1st Author's Affiliation |
Hokkaido University (Hokkaido Univ.) |
| 2nd Author's Name |
Keisuke Maeda |
| 2nd Author's Affiliation |
Hokkaido University (Hokkaido Univ.) |
| 3rd Author's Name |
Takahiro Ogawa |
| 3rd Author's Affiliation |
Hokkaido University (Hokkaido Univ.) |
| 4th Author's Name |
Miki Haseyama |
| 4th Author's Affiliation |
Hokkaido University (Hokkaido Univ.) |
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| Speaker |
Author-1 |
| Date Time |
2022-02-21 15:05:00 |
| Presentation Time |
15 minutes |
| Registration for |
ME |
| Paper # |
MMS2022-26, ME2022-51, AIT2022-26 |
| Volume (vol) |
vol.46 |
| Number (no) |
no.6 |
| Page |
pp.181-186 |
| #Pages |
6 |
| Date of Issue |
2022-02-14 (MMS, ME, AIT) |