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WALDO: Wide Area Localization of Depicted Objects


This project addresses the problem of automatically estimating the geographic location of an image or video. I am leading the University of Kentucky component of a larger project that aims to build a complete system for this task. Our research focus is on using geometric and temporal constraints to improve accuracy and reduce computational costs and finding relationships between ground-level views and satellite imagery.

Additional Resources

Related Publication(s)

  1. Zhai M., Workman S., Jacobs N. 2016. Camera Geo-Calibration using an MCMC Approach. In: IEEE International Conference on Image Processing (ICIP). website bibtex
  2. PDF Workman S., Zhai M., Jacobs N. 2016. Horizon Lines in the Wild. In: British Machine Vision Conference (BMVC). website bibtex
  3. PDF Workman S., Souvenir R., Jacobs N. 2015. Wide-Area Image Geolocalization with Aerial Reference Imagery. In: IEEE International Conference on Computer Vision (ICCV). 1–9. website code bibtex
  4. PDF Workman S., Jacobs N. 2015. On the Location Dependence of Convolutional Neural Network Features. In: IEEE/ISPRS Workshop: Looking from above: When Earth observation meets vision (EARTHVISION). 1–9. bibtex
  5. Workman S., Mihail RP., Jacobs N. 2014. A Pot of Gold: Rainbows as a Calibration Cue. In: European Conference on Computer Vision (ECCV). 820–835. website bibtex


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