SVM Based Classification of Seven Nature Objects for Anytime, Anywhere Digital Photo Annotation
| Autor: | Seong Joon Yoo, Chull Hwan Song |
|---|---|
| Rok vydání: | 2007 |
| Předmět: |
Information retrieval
business.product_category Ubiquitous computing Contextual image classification Computer science business.industry ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Digital photography Support vector machine Annotation Digital image Histogram Computer vision Artificial intelligence business Digital camera |
| Zdroj: | MUE |
| DOI: | 10.1109/mue.2007.199 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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