2016/01/18 by Vinay Bettadapura, Bettadapura, Vinay, Daniel C. Castro +4 · 1 citation
Computer Science · #Advanced Image and Video Retrieval Techniques #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Video Analysis and Summarization #Visual Attention and Saliency Detection #cs.CV
paper · pdf · doi:10.48550/arxiv.1601.04406
arxiv created 2016/01/18 · openalex publication_date 2016/01/18 · arxiv updated 2016/01/19 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.