Digital photo classification methodology for groups of photographers

Abstract

Digital cameras have become an essential product when traveling or attending events. Because of its popularity and low cost, it is increasingly likely that more than one camera will be used at an event. The total number of photos captured is also increasing. Although the cost of digital photographs is low, managing numerous digital photos is burdensome to most users. Thus, an intelligent management tool for digital photos is required. In this paper, we propose novel clustering algorithms for concurrent digital photos obtained from multiple cameras. Since previous studies only considered a single user’s photo collection, they are not applicable to concurrent photos obtained from a group of photographers. To handle this situation, we define temporal/spatial combined clustering for the set of group photos taken from different cameras. If photos are submitted from a camera whose user has shown a preference between spatial and temporal clustering, we can obtain customized clustering output from other photo sets according to the reference clustering characteristics. We also propose unsupervised methods for general clustering output. Input concurrent photos are processed without a user’s true clusters, which can be a burden when the number of photos in the true clusters is huge. We tested our methods via more than one thousand photos taken by tourist groups. The final result was satisfactory compared to previous methods based on temporal (spatial) criteria only.