Event-centric View of Consumer Image Collections

Benchmark and ground truth databases are critical for evaluating imaging- and event-based algorithms, but such databases can be time consuming to create, cannot be representative of all real-life consumer image collections, and do not necessarily provide feedback on the general utility of an imperfect algorithm applied to real-life data. An alternative solution is needed to complement evaluation by benchmark and ground truth databases. We designed and developed event analyzer as a tool to meet this need. Event analyzer combines data visualization of metadata with event and image retrieval results in a way that enables researchers to easily review data trends, quickly filter and select data, see relationships between metadata values, and visually scan retrieved results to determine correctness. In this paper, we describe the tool and discuss how it can and has been used to analyze real-life consumer collections in an event-centric manner.