Indexing media by personal events

We are addressing the problem of organizing and indexing one's personal media. Recent approaches of media indexing use events as media aggregators, but do not fully consider the context in which the media asset has been produced and do not take the personal perspective of the user into account. To this end, we propose a new paradigm for the automated indexing of social media based on the the notion of personal events. We reveal both personal habits of a user by analyzing the patterns of capturing images in space and time, while we also improve the understanding of photos over the years by learning the user's personal behavior. Our fully automatic and computationally inexpensive approach outperforms the state of the art in event-based media indexing. Moreover, we aim to push two main ideas to the problem: (1) We automatically assign the events to routine locations and non-routine locations. This gives the basic nature of events. (2) We hierarchically arrange events at non-routine locati...