Publication Type
Journal Article
Version
acceptedVersion
Publication Date
11-2016
Abstract
The introduction of wearable video cameras (e.g., GoPro) in the consumer market has promoted video life-logging, motivating users to generate large amounts of video data. This increasing flow of first-person video has led to a growing need for automatic video summarization adapted to the characteristics and applications of egocentric video. With this paper, we provide the first comprehensive survey of the techniques used specifically to summarize egocentric videos. We present a framework for first-person view summarization and compare the segmentation methods and selection algorithms used by the related work in the literature. Next, we describe the existing egocentric video datasets suitable for summarization and, then, the various evaluation methods. Finally, we analyze the challenges and opportunities in the field and propose new lines of research.
Keywords
Egocentric Vision, First Person View, Survey, Video Summarization
Discipline
Computer Engineering | Databases and Information Systems | OS and Networks
Research Areas
Data Science and Engineering
Publication
IEEE Transactions on Human-Machine Systems
Volume
47
Issue
1
First Page
65
Last Page
76
ISSN
2168-2291
Identifier
10.1109/THMS.2016.2623480
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
GARCIA DEL MOLINO, Ana; TAN, Cheston; LIM, Joo-Hwee; and TAN, Ah-hwee.
Summarization of egocentric videos: A comprehensive survey. (2016). IEEE Transactions on Human-Machine Systems. 47, (1), 65-76.
Available at: https://ink.library.smu.edu.sg/sis_research/5197
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1109/THMS.2016.2623480
Included in
Computer Engineering Commons, Databases and Information Systems Commons, OS and Networks Commons