Automatic mobile photo tagging using context

The market of smartphones has been exploding, and taking pictures is a basic, maybe one of the most important functions of a smartphone. In this paper we address the problem of managing a large amount of mobile photos by automatically tagging the photos, so they can be easily browsed or searched later. Unlike other content-based photo tagging approaches, this paper's main contribution is to explore an alternative opportunity of automatic photo tagging using contextual information. Both clustering and similarity-based approaches were studied for photo tagging using context such as date, time, location, environment noise, and human faces. The results show that there are intrinsic connections between contextual information and photo tags, and similarity-based approach outperforms clustering-based tagging significantly.