Research on Vocabulary Sizes and Codebook Universality
Joint Authors
Hou, Jian
Karimi, Hamid Reza
Liu, Wei-Xue
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-02-26
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
Codebook is an effective image representation method.
By clustering in local image descriptors, a codebook is shown to be a distinctive image feature and widely applied in object classification.
In almost all existing works on codebooks, the building of the visual vocabulary follows a basic routine, that is, extracting local image descriptors and clustering with a user-designated number of clusters.
The problem with this routine lies in that building a codebook for each single dataset is not efficient.
In order to deal with this problem, we investigate the influence of vocabulary sizes on classification performance and vocabulary universality with the kNN classifier.
Experimental results indicate that, under the condition that the vocabulary size is large enough, the vocabularies built from different datasets are exchangeable and universal.
American Psychological Association (APA)
Liu, Wei-Xue& Hou, Jian& Karimi, Hamid Reza. 2014. Research on Vocabulary Sizes and Codebook Universality. Abstract and Applied Analysis،Vol. 2014, no. 2014, pp.1-7.
https://search.emarefa.net/detail/BIM-1014603
Modern Language Association (MLA)
Liu, Wei-Xue…[et al.]. Research on Vocabulary Sizes and Codebook Universality. Abstract and Applied Analysis No. 2014 (2014), pp.1-7.
https://search.emarefa.net/detail/BIM-1014603
American Medical Association (AMA)
Liu, Wei-Xue& Hou, Jian& Karimi, Hamid Reza. Research on Vocabulary Sizes and Codebook Universality. Abstract and Applied Analysis. 2014. Vol. 2014, no. 2014, pp.1-7.
https://search.emarefa.net/detail/BIM-1014603
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1014603