  We present an approach for identifying picturesque highlights from large
amounts of egocentric video data. Given a set of egocentric videos captured
over the course of a vacation, our method analyzes the videos and looks for
images that have good picturesque and artistic properties. We introduce novel
techniques to automatically determine aesthetic features such as composition,
symmetry and color vibrancy in egocentric videos and rank the video frames
based on their photographic qualities to generate highlights. Our approach also
uses contextual information such as GPS, when available, to assess the relative
importance of each geographic location where the vacation videos were shot.
Furthermore, we specifically leverage the properties of egocentric videos to
improve our highlight detection. We demonstrate results on a new egocentric
vacation dataset which includes 26.5 hours of videos taken over a 14 day
vacation that spans many famous tourist destinations and also provide results
from a user-study to access our results.
