Paper (WACV 2016) "Discovering Picturesque Highlights from Egocentric Vacation Videos"

Paper

  • D. Castro, V. Bettadapura, and Irfan Essa (2016), “Discovering Picturesque Highlights from Egocentric Vacation Video,” in IEEE Winter Conference on Applications of Computer Vision (WACV), 2016. [PDF] [WEBSITE] [arXiv] [BIBTEX]
    @InProceedings{ 2016-Castro-DPHFEVV,
    arxiv = {http://arxiv.org/abs/1601.04406},
    author  = {Daniel Castro and Vinay Bettadapura and Irfan
    Essa},
    booktitle  = {{IEEE Winter Conference on Applications of Computer
    Vision (WACV)}},
    month = {March},
    pdf = {http://www.cc.gatech.edu/~irfan/p/2016-Castro-DPHFEVV.pdf},
    title = {Discovering Picturesque Highlights from Egocentric
    Vacation Video},
    url = {http://www.cc.gatech.edu/cpl/projects/egocentrichighlights/},
    year = {2016}
    }

Abstract

2016-Castro-DPHFEVV

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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