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UCSD Computer Vision

Image Based Geolocalization

Tsung-Yi Lin, Hani Altwaijry, Serge Belongie


Synopsis

Image-based Geo-localization is a relatively new and challenging problem in Computer Vision. It is simply defined as: given a photo, where was it taken? In this project, we are interested in: 1) localizing a ground-level image with an aerial imagery gallery by cross-view image matching 2) designing a human-in-the-loop system to learn and match the geographically meaningful visual patterns for geolocalization 3) correspondence matching for images under ultra-wide baseline conditions.


Non UCSD Vision People also Involved

James Hays


Related Publications

2014
Altwaijry H., Moghimi M., Belongie S., "Recognizing Locations with Google Glass: A Case Study", IEEE Winter Conference on Applications of Computer Vision (WACV), Steamboat Springs, Colorado, March, 2014. [BibTex][pdf]
2013
Lin T., Belongie S., Hays J., "Cross-view Image Geolocalization", IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Portland, OR, June, 2013. [BibTex][pdf]
Altwaijry H., Belongie S., "Ultra-wide Baseline Aerial Imagery Matching in Urban Environments", British Machine Vision Conference (BMVC), Bristol, September, 2013. [BibTex][pdf]