Bag-of-Words Representation in Image Annotation : A Review
Author
Source
Issue
Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-19, 19 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2012-11-29
Country of Publication
Egypt
No. of Pages
19
Main Subjects
Abstract EN
Content-based image retrieval (CBIR) systems require users to query images by their low-level visual content; this not only makes it hard for users to formulate queries, but also can lead to unsatisfied retrieval results.
To this end, image annotation was proposed.
The aim of image annotation is to automatically assign keywords to images, so image retrieval users are able to query images by keywords.
Image annotation can be regarded as the image classification problem: that images are represented by some low-level features and some supervised learning techniques are used to learn the mapping between low-level features and high-level concepts (i.e., class labels).
One of the most widely used feature representation methods is bag-of-words (BoW).
This paper reviews related works based on the issues of improving and/or applying BoW for image annotation.
Moreover, many recent works (from 2006 to 2012) are compared in terms of the methodology of BoW feature generation and experimental design.
In addition, several different issues in using BoW are discussed, and some important issues for future research are discussed.
American Psychological Association (APA)
Tsai, Chih-Fong. 2012. Bag-of-Words Representation in Image Annotation : A Review. ISRN Artificial Intelligence،Vol. 2012, no. 2012, pp.1-19.
https://search.emarefa.net/detail/BIM-467259
Modern Language Association (MLA)
Tsai, Chih-Fong. Bag-of-Words Representation in Image Annotation : A Review. ISRN Artificial Intelligence No. 2012 (2012), pp.1-19.
https://search.emarefa.net/detail/BIM-467259
American Medical Association (AMA)
Tsai, Chih-Fong. Bag-of-Words Representation in Image Annotation : A Review. ISRN Artificial Intelligence. 2012. Vol. 2012, no. 2012, pp.1-19.
https://search.emarefa.net/detail/BIM-467259
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-467259