Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples
The Journal of Machine Learning Research
Proceedings of the 15th international conference on Multimedia
Generating diverse and representative image search results for landmarks
Proceedings of the 17th international conference on World Wide Web
Spirittagger: a geo-aware tag suggestion tool mined from flickr
MIR '08 Proceedings of the 1st ACM international conference on Multimedia information retrieval
Proceedings of the 18th international conference on World wide web
IEEE Transactions on Circuits and Systems for Video Technology
Exploring Geotagged images for land-use classification
Proceedings of the ACM multimedia 2012 workshop on Geotagging and its applications in multimedia
Proceedings of the 5th ACM SIGSPATIAL International Workshop on Location-Based Social Networks
Hi-index | 0.00 |
Volunteered geographic information such as that available in blogs, wikis, social networking sites, and community contributed photo collections is enabling new applications. This work investigates the use of georeferenced images from a popular photo sharing site for proximate sensing. In particular, we use computer vision and machine learning techniques to perform land cover classification based on the content of the georeferenced images. We evaluate the results using a ground truth dataset from the National Land Cover Database. We demonstrate that our approach can achieve upwards of 75% classification accuracy in a completely automated fashion.