Paper
8 December 2015 An unsupervised method for summarizing egocentric sport videos
Hamed Habibi Aghdam, Elnaz Jahani Heravi, Domenec Puig
Author Affiliations +
Proceedings Volume 9875, Eighth International Conference on Machine Vision (ICMV 2015); 98751N (2015) https://doi.org/10.1117/12.2228883
Event: Eighth International Conference on Machine Vision, 2015, Barcelona, Spain
Abstract
People are getting more interested to record their sport activities using head-worn or hand-held cameras. This type of videos which is called egocentric sport videos has different motion and appearance patterns compared with life-logging videos. While a life-logging video can be defined in terms of well-defined human-object interactions, notwithstanding, it is not trivial to describe egocentric sport videos using well-defined activities. For this reason, summarizing egocentric sport videos based on human-object interaction might fail to produce meaningful results. In this paper, we propose an unsupervised method for summarizing egocentric videos by identifying the key-frames of the video. Our method utilizes both appearance and motion information and it automatically finds the number of the key-frames. Our blind user study on the new dataset collected from YouTube shows that in 93:5% cases, the users choose the proposed method as their first video summary choice. In addition, our method is within the top 2 choices of the users in 99% of studies.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Hamed Habibi Aghdam, Elnaz Jahani Heravi, and Domenec Puig "An unsupervised method for summarizing egocentric sport videos", Proc. SPIE 9875, Eighth International Conference on Machine Vision (ICMV 2015), 98751N (8 December 2015); https://doi.org/10.1117/12.2228883
Lens.org Logo
CITATIONS
Cited by 1 scholarly publication.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Video

Associative arrays

Cameras

Video coding

Image processing

Error analysis

RGB color model

RELATED CONTENT

Study of landmarks estimation stability produced by AAM
Proceedings of SPIE (June 26 2017)
Moving-objects extraction in diving video
Proceedings of SPIE (May 07 2003)
Domain-based multiple description coding of images and video
Proceedings of SPIE (January 04 2002)
Temporal coherency for video tone mapping
Proceedings of SPIE (October 15 2012)

Back to Top