Building geo-aware tag features for image classification
Shuai Liao, Xirong Li, Xiaoxu Wang, Xiaoyong Du · 2014
Given the proliferation of geo-tagged images, geo-aware image classification is an emerging topic. To derive a better image representation, tag features which represents an image as a histogram of tags are recently introduced. However, it is unclear whether geo tags can improve the tag features. To resolve the uncertainty, this paper studies geo-aware tag features. Our work is based on previous work which builds tag features by propagating tags from visual neighbors retrieved from many user-tagged images. What is different is that we build tag features by tag propagation from the union of visual and geo neighbors. This simple modification makes the new tag feature both content-aware and geo-aware. Using 1M Flickr images as a source set to construct the tag feature, experiments on the public NUS-WIDE set justify our proposal. The geo-aware tag feature outperforms the previous tag feature and a standard bag of visual words feature. Our geo-aware image classification system beats a recent alternative. For its simplicity and effectiveness, we consider the proposed tag feature promising for geo-aware image classification.