To Keep or not to Keep

Abstract

When selecting important photos from a personal photo collection - e.g. for creating an enjoyable sub-collection for revisiting or preservation - photos are not considered in isolation. Therefore, collection-level criteria are also taken into account by automated photo selection methods. However, the typical two-step process of first clustering and subsequently picking from the clusters seems to overstress coverage as a criterion when applied to the task of selecting the photos most important to a user. We, therefore, propose a novel expectation-oriented photo selection method, which combines a variety of collection-level and image-level selection criteria in a flexible way. In our evaluation, which is based on large real-world personal photo collections with overall more than 18,000 images, we show that our method outperforms state-of-the-art photo selection methods. In addition, the proposed method does not rely on any manual annotations, making it applicable in realistic settings of personal photo collections.