DocumentCode
2558614
Title
SVM Based Classification of Seven Nature Objects for Anytime, Anywhere Digital Photo Annotation
Author
Song, Chull Hwan ; Yoo, Seong Joon
Author_Institution
Sejong Univ., Seoul
fYear
2007
fDate
26-28 April 2007
Firstpage
1249
Lastpage
1254
Abstract
This paper proposes a method that can be utilized for automatically annotating digital photos anytime, anywhere. A digital camera or an annotation server connected to the digital camera through a ubiquitous computing network can automatically annotate captured photos using the proposed method. Annotating digital images is not a new research problem. We have developed a novel method of classifying seven nature objects from digital images. Thus, this paper describes the method and shows that it is superior to previous methods of classifying nature objects.
Keywords
image classification; support vector machines; ubiquitous computing; video cameras; SVM based classification; automatic digital photo annotation; digital camera; digital image annotation; nature object classification; ubiquitous computing network; Digital cameras; Digital images; Histograms; Humans; Internet; Layout; Principal component analysis; Support vector machine classification; Support vector machines; Ubiquitous computing;
fLanguage
English
Publisher
ieee
Conference_Titel
Multimedia and Ubiquitous Engineering, 2007. MUE '07. International Conference on
Conference_Location
Seoul
Print_ISBN
0-7695-2777-9
Type
conf
DOI
10.1109/MUE.2007.199
Filename
4197451
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