Paper in WACV 2016 on “Discovering Picturesque Highlights from Egocentric Vacation Videos”


Daniel Castro, Vinay Bettadapura, Irfan Essa

Discovering Picturesque Highlights from Egocentric Vacation Video Proceedings Article

In: IEEE Winter Conference on Applications of Computer Vision (WACV), 2016.

Abstract | Links | BibTeX | Tags: computational photography, computational video, computer vision, WACV


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.

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