loading...
 This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
2007 International Conference on Multimedia and Ubiquitous Engineering (MUE'07)
SVM Based Classification of Seven Nature Objects for Anytime, Anywhere Digital Photo Annotation
Seoul, Korea
April 26-April 28
ISBN: 0-7695-2777-9
Chull Hwan Song, Sejong University, 98 Gunja, Gwangjin Seoul, Korea
Seong Joon Yoo, Sejong University, 98 Gunja, Gwangjin Seoul, Korea
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.
Citation:
Chull Hwan Song, Seong Joon Yoo, "SVM Based Classification of Seven Nature Objects for Anytime, Anywhere Digital Photo Annotation," mue, pp.1249-1254, 2007 International Conference on Multimedia and Ubiquitous Engineering (MUE'07), 2007
Usage of this product signifies your acceptance of the Terms of Use.