Discovering Picturesque Highlights from Egocentric Vacation Videos
Vinay Bettadapura, Daniel Castro, Irfan Essa

TL;DR
This paper introduces a novel method for automatically extracting picturesque highlights from egocentric vacation videos by analyzing aesthetic qualities and contextual information, validated on a new dataset with user-study support.
Contribution
It presents new techniques for assessing aesthetic features in egocentric videos and integrates contextual data to improve highlight detection, a novel approach in vacation video summarization.
Findings
Effective identification of picturesque highlights in egocentric videos
Incorporation of GPS data enhances highlight relevance
Validated results through a user-study on a new dataset
Abstract
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…
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Taxonomy
TopicsVideo Analysis and Summarization · Advanced Image and Video Retrieval Techniques · Visual Attention and Saliency Detection
