Abstract
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
Keywords
Cite this article
@article{cai-1808,
author = {Chull Hwan Song and Seong Joon Yoo and Chee Sun Won and Hyoung Gon Kim},
title = {SVM Based Indoor/Mixed/Outdoor Classification for Digital Photo Annotation in a Ubiquitous Computing Environment},
journal = {Computing and Informatics},
volume = {27},
number = {5},
pages = {757--767},
year = {2008},
issn = {1335-9150},
url = {https://cai.type.sk/content/2008/5/svm-based-indoor-mixed-outdoor-classification-for-digital-photo-annotation-in-a-ubiquitous-computing-environment/}
}
TY - JOUR AU - Chull Hwan Song AU - Seong Joon Yoo AU - Chee Sun Won AU - Hyoung Gon Kim TI - SVM Based Indoor/Mixed/Outdoor Classification for Digital Photo Annotation in a Ubiquitous Computing Environment JO - Computing and Informatics VL - 27 IS - 5 SP - 757 EP - 767 PY - 2008 SN - 1335-9150 UR - https://cai.type.sk/content/2008/5/svm-based-indoor-mixed-outdoor-classification-for-digital-photo-annotation-in-a-ubiquitous-computing-environment/ KW - Image classification KW - support vector machine KW - low-level feature extraction ER -
Song, C. H., Yoo, S. J., Won, C. S., & Kim, H. G. (2008). SVM Based Indoor/Mixed/Outdoor Classification for Digital Photo Annotation in a Ubiquitous Computing Environment. Computing and Informatics, 27(5), 757–767. https://cai.type.sk/content/2008/5/svm-based-indoor-mixed-outdoor-classification-for-digital-photo-annotation-in-a-ubiquitous-computing-environment/