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Journal Article Improved Quality Keyframe Selection Method for HD Video
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Authors
Hyeon Seok Yang, Jong Min Lee, Woojin Jeong, Seung-Hee Kim, Sun-Joong Kim, Young Shik Moon
Issue Date
2019-06
Citation
KSII Transactions on Internet and Information Systems, v.13, no.6, pp.3074-3091
ISSN
1976-7277
Publisher
한국인터넷정보학회
Language
English
Type
Journal Article
DOI
https://dx.doi.org/10.3837/tiis.2019.06.017
Abstract
With the widespread use of the Internet, services for providing large-capacity multimedia data such as video-on-demand (VOD) services and video uploading sites have greatly increased. VOD service providers want to be able to provide users with high-quality keyframes of high quality videos within a few minutes after the broadcast ends. However, existing keyframe extraction tends to select keyframes whose quality as a keyframe is insufficiently considered, and it takes a long computation time because it does not consider an HD class image. In this paper, we propose a keyframe selection method that flexibly applies multiple keyframe quality metrics and improves the computation time. The main procedure is as follows. After shot boundary detection is performed, the first frames are extracted as initial keyframes. The user sets evaluation metrics and priorities by considering the genre and attributes of the video. According to the evaluation metrics and the priority, the low-quality keyframe is selected as a replacement target. The replacement target keyframe is replaced with a high-quality frame in the shot. The proposed method was subjectively evaluated by 23 votes. Approximately 45% of the replaced keyframes were improved and about 18% of the replaced keyframes were adversely affected. Also, it took about 10 minutes to complete the summary of one hour video, which resulted in a reduction of more than 44.5% of the execution time.
KSP Keywords
High-quality, Keyframe Extraction, Keyframe selection, Large capacity, Multimedia data, Quality Metrics, Selection method, Service Provider, Shot boundary detection, VOD service, Video on Demand