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.

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)