文章基本信息

标题：SVM Based Indoor/Mixed/Outdoor Classification for Digital Photo Annotation in a Ubiquitous Computing Environment
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作者：Song, Chull Hwan ; Yoo, Seong Joon ; Won, Chee Sun 等
期刊名称：COMPUTING AND INFORMATICS
印刷版ISSN：1335-9150
出版年度：2008
卷号：27
期号：5
页码：757-767
语种：English
出版社：COMPUTING AND INFORMATICS
摘要：This paper extends our previous framework for digital photo annotation by adding noble approach of indoor/mixed/outdoor image classification. We propose the best feature vectors for a support vector machine based indoor/mixed/ outdoor image classification. While previous research classifies photographs into indoor and outdoor, this study extends into three types, including indoor, mixed, and outdoor classes. This three-class method improves the performance of outdoor classification. This classification scheme showed 5--10% higher performance than previous research. This method is one of the components for digital image annotation. A digital camera or an annotation server connected to a ubiquitous computing network can automatically annotate captured photos using the proposed method.
关键词：Image classification; support vector machine; low-level feature extraction