Survey on visual sentiment analysis. Issue 8 (14th May 2020)
- Record Type:
- Journal Article
- Title:
- Survey on visual sentiment analysis. Issue 8 (14th May 2020)
- Main Title:
- Survey on visual sentiment analysis
- Authors:
- Ortis, Alessandro
Farinella, Giovanni Maria
Battiato, Sebastiano - Abstract:
- Abstract : Visual Sentiment Analysis aims to understand how images affect people, in terms of evoked emotions. Although this field is rather new, a broad range of techniques have been developed for various data sources and problems, resulting in a large body of research. This paper reviews pertinent publications and tries to present an exhaustive overview of the field. After a description of the task and the related applications, the subject is tackled under different main headings. The paper also describes principles of design of general Visual Sentiment Analysis systems from three main points of view: emotional models, dataset definition, feature design. A formalization of the problem is discussed, considering different levels of granularity, as well as the components that can affect the sentiment toward an image in different ways. To this aim, this paper considers a structured formalization of the problem which is usually used for the analysis of text, and discusses it's suitability in the context of Visual Sentiment Analysis. The paper also includes a description of new challenges, the evaluation from the viewpoint of progress toward more sophisticated systems and related practical applications, as well as a summary of the insights resulting from this study.
- Is Part Of:
- IET image processing. Volume 14:Issue 8(2020)
- Journal:
- IET image processing
- Issue:
- Volume 14:Issue 8(2020)
- Issue Display:
- Volume 14, Issue 8 (2020)
- Year:
- 2020
- Volume:
- 14
- Issue:
- 8
- Issue Sort Value:
- 2020-0014-0008-0000
- Page Start:
- 1440
- Page End:
- 1456
- Publication Date:
- 2020-05-14
- Subjects:
- sentiment analysis -- publishing
data sources -- general Visual Sentiment Analysis systems -- pertinent publications -- text analysis -- emotional models -- dataset definition -- feature design
Image processing -- Periodicals
621.36705 - Journal URLs:
- http://digital-library.theiet.org/content/journals/iet-ipr ↗
http://ieeexplore.ieee.org/servlet/opac?punumber=4149689 ↗
http://www.ietdl.org/IET-IPR ↗
https://ietresearch.onlinelibrary.wiley.com/journal/17519667 ↗
http://www.theiet.org/ ↗ - DOI:
- 10.1049/iet-ipr.2019.1270 ↗
- Languages:
- English
- ISSNs:
- 1751-9659
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4363.252600
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 16611.xml