JIPS (한국정보처리학회)
Current Result Document :
| 한글제목(Korean Title) |
A Survey on Image Emotion Recognition |
| 영문제목(English Title) |
A Survey on Image Emotion Recognition |
| 저자(Author) |
Guangzhe Zhao
Hanting Yang
Bing Tu
Lei Zhang
|
| 원문수록처(Citation) |
VOL 17 NO. 05 PP. 1138 ~ 1156 (2021. 10) |
한글내용
(Korean Abstract) |
|
영문내용
(English Abstract) |
Emotional semantics are the highest level of semantics that can be extracted from an image. Constructing a system that can automatically recognize the emotional semantics from images will be significant for marketing, smart healthcare, and deep human-computer interaction. To understand the direction of image emotion recognition as well as the general research methods, we summarize the current development trends and shed light on potential future research. The primary contributions of this paper are as follows. We investigate the color, texture, shape and contour features used for emotional semantics extraction. We establish two models that map images into emotional space and introduce in detail the various processes in the image emotional semantic recognition framework. We also discuss important datasets and useful applications in the field such as garment image and image retrieval. We conclude with a brief discussion about future research trends. |
| 키워드(Keyword) |
Emotion Semantics
Image Emotion Recognition
Image Feature Extraction
Machine Learning
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| 파일첨부 |
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