Structural epitome: a way to summarize one's visual experience

In order to study the properties of total visual input in humans, a single subject wore a camera for two weeks capturing, on average, an image every 20 seconds (www.research.microsoft.com/ The resulting new dataset contains a mix of indoor and outdoor scenes as well as numerous foreground objects. Our first analysis goal is to create a visual summary of the subject's two weeks of life using unsupervised algorithms that would automatically discover recurrent scenes, familiar faces or common actions. Photosynth) or appearance-based clustering models (e.g. the epitome), is impractical due to either the large dataset size or the dramatic variation in the lighting conditions. As a remedy to these problems, we introduce a novel image representation, the "stel epitome," and an associated efficient learning algorithm.