
Proceedings Paper
Webcam classification using simple featuresFormat | Member Price | Non-Member Price |
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Paper Abstract
Thousands of sensors are connected to the Internet and many of these sensors are cameras. The “Internet of
Things” will contain many “things” that are image sensors. This vast network of distributed cameras (i.e. web
cams) will continue to exponentially grow. In this paper we examine simple methods to classify an image from
a web cam as “indoor/outdoor” and having “people/no people” based on simple features. We use four types of
image features to classify an image as indoor/outdoor: color, edge, line, and text. To classify an image as having
people/no people we use HOG and texture features. The features are weighted based on their significance and
combined. A support vector machine is used for classification. Our system with feature weighting and feature
combination yields 95.5% accuracy.
Paper Details
Date Published: 12 March 2015
PDF: 12 pages
Proc. SPIE 9401, Computational Imaging XIII, 94010G (12 March 2015); doi: 10.1117/12.2083417
Published in SPIE Proceedings Vol. 9401:
Computational Imaging XIII
Charles A. Bouman; Ken D. Sauer, Editor(s)
PDF: 12 pages
Proc. SPIE 9401, Computational Imaging XIII, 94010G (12 March 2015); doi: 10.1117/12.2083417
Show Author Affiliations
Thitiporn Pramoun, King Mongkut’s Univ. of Technology Thonburi (Thailand)
Jeehyun Choe, Purdue Univ. (United States)
He Li, Purdue Univ. (United States)
Qingshuang Chen, Purdue Univ. (United States)
Jeehyun Choe, Purdue Univ. (United States)
He Li, Purdue Univ. (United States)
Qingshuang Chen, Purdue Univ. (United States)
Thumrongrat Amornraksa, King Mongkut’s Univ. of Technology Thonburi (Thailand)
Yung-Hsiang Lu, Purdue Univ. (United States)
Edward J. Delp III, Purdue Univ. (United States)
Yung-Hsiang Lu, Purdue Univ. (United States)
Edward J. Delp III, Purdue Univ. (United States)
Published in SPIE Proceedings Vol. 9401:
Computational Imaging XIII
Charles A. Bouman; Ken D. Sauer, Editor(s)
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