CBGIR: content-based geographic image retrieval

Authors:
Shawn Newsam;Daniel Leung;Oscar Caballero;Justin Floreza;Jesus Pulido
Affiliations:
University of California at Merced;University of California at Merced;University of California at Merced;University of California at Merced;University of California at Merced
Venue:
Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems
Year:
2010

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Abstract

We describe and demonstrate CBGIR, a web-based system for performing content-based image retrieval in large sets of high-resolution overhead images. The system provides a familiar Google Maps interface to navigate the images and select regions of interest. A query-by-example paradigm is used to retrieve the most visually similar images to this region from a large target set of image tiles. Similarity can be computed with respect to a number of visual features including color, texture, and local invariant descriptors. We describe the salient components of the system and provide sample retrieval results.