Sports image classification through Bayesian classifier

Youna Jung, Een Jun Hwang, Wonil Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)

Abstract

Most documents on the web today contain image as well as text data. So far, classification of images has been dependent on the annotation. For the more efficient and accurate classification, not only textual data but also image contents should be considered. In this paper, we propose a novel method for classifying specific image data; sports images. The proposed method is based on the Bayesian framework and employs four important color features to exploit the properties of sports images.

Original languageEnglish
Title of host publicationLecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)
EditorsR. Conejo, M. Urretavizcaya, J.-L. Perez-de-la-Cruz
Pages546-555
Number of pages10
Volume3040
Publication statusPublished - 2004
Externally publishedYes
Event10th Conference of the Spanish Association for Artificial Intelligence, CAEPIA, 2003 and 5th Conference on Technology Transfer, TTIA 2003 - San Sebastian, Spain
Duration: 2003 Nov 122003 Nov 14

Other

Other10th Conference of the Spanish Association for Artificial Intelligence, CAEPIA, 2003 and 5th Conference on Technology Transfer, TTIA 2003
CountrySpain
CitySan Sebastian
Period03/11/1203/11/14

ASJC Scopus subject areas

  • Hardware and Architecture

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  • Cite this

    Jung, Y., Hwang, E. J., & Kim, W. (2004). Sports image classification through Bayesian classifier. In R. Conejo, M. Urretavizcaya, & J-L. Perez-de-la-Cruz (Eds.), Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science) (Vol. 3040, pp. 546-555)