Transition effect detection for extracting highlights in baseball videos

NCUIR > College of Electrical Engineering & Computer Science > Department of Computer Science and information Engineering > journal & Dissertation > Item 987654321/107449

Please use this identifier to cite or link to this item: https://ir.lib.ncu.edu.tw/handle/987654321/107449

Title:	Transition effect detection for extracting highlights in baseball videos
Authors:	蘇柏齊;Su, Po-Chyi;Lan, Chi-Heng;Wu, Chin-Song;Zeng, Zi-Xin;Chen, Wei-Yu
Contributors:	資訊電機學院資訊工程學系
Keywords:	Biometrics;Engineering;Image Processing and Computer Vision;Pattern Recognition;Signal,Image and Speech Processing
Date:	2013-11-11
Issue Date:	2026-04-23 14:13:12 (UTC+8)
Publisher:	Springer Publishing Company;Cham: Springer International Publishing
Abstract:	摘要： In this research, a transition effect detection scheme for identifying possible highlight segments in baseball videos will be presented. The effects that are inserted manually by the broadcasters for signaling the slow-motion segments will be extracted and the frames containing such effects can serve as anchor positions for further processing. A set of video segments will first be chosen to construct the ‘transition effect template’ for the archived video. The candidate frames will be compared with this template for searching the slow-motion video segments. In baseball videos, we further construct the ‘pitching view template’ so that the starting positions of the video segments of interest can be located. By processing these segments only, we may further employ such method as hidden Markov model to classify their content. The major contribution of this research is the usage of compressed-domain features to achieve the efficiency. The experimental results show the feasibility of the proposed scheme. 其他題名： J Image Video Proc 出版者： Cham: Springer International Publishing 出版日期： 2013-05-04 出處： EURASIP journal on image and video processing, 2013-05, Vol.2013 (1), Article 27 資源來源： Springer Nature Open Access Journals (NTUSG) 版權： Su et al.; licensee Springer. 2013. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 識別號： ISSN: 1687-5281 識別號： ISSN: 1687-5176 識別號： EISSN: 1687-5281 識別號： DOI: 10.1186/1687-5281-2013-27
Appears in Collections:	[Department of Computer Science and information Engineering] journal & Dissertation

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