Hossam M. Zawbaa, Nashwa El-Bendary, Aboul Ella Hassanien, Tai-hoon Kim
언어
영어(ENG)
URL
https://www.earticle.net/Article/A202122
※ 원문제공기관과의 협약기간이 종료되어 열람이 제한될 수 있습니다.
원문정보
초록
영어
Many soccer fans prefer to watch a summary of football games as watching a whole soccer match needs a lot of time. Traditionally, soccer videos were analyzed manually, however this costs valuable time. Therefore, it is necessary to have a tool for doing the video anal- ysis and summarization job automatically. Automatic soccer video summarization is about extracting important events from soccer matches in order to produce general summaries for the most important moments in which soccer viewers may be interested. This paper presents a machine learning (ML) based event detection and summarization system for em- phasizing important events during soccer matches. The proposed system rstly segments the whole video stream into small video shots, then it classies the resulted shots into dierent shot-type classes. Afterwards, the system applies two machine learning algorithms, namely; support vector machine (SVM) and articial neural network (ANN), for emphasizing impor- tant segments with logo appearance with addition to detecting the caption region providing information about the score of the game. Subsequently, the system detects vertical goal posts and goal net. Finally, the most important events during the match are highlighted in the resulted soccer video summary. Experiments on real soccer videos demonstrate encourag- ing results. The proposed approach greatly reduces workload and enhances the accuracy of summarizing soccer video matches with reference to both recall and precision performance measurement criteria.
목차
Abstract 1. Background and Related Work 2. Machine Learning (ML): A Brief Background 2.1 Articial Neural Network (ANN) 2.2 Support Vector Machine (SVM) 3. The Proposed Soccer Video Summarization Approach 3.1 Pre-processing Phase 3.2 Shot Processing Phase 3.3 Replay Detection Phase 3.4 Excitement Event Detection Phase 3.5 Event Detection and Summarization Phase 4. Experimental Results 5. Conclusions and Future Works References
키워드
support vector machine (SVM)articial neural network (ANN)machine learning (ML)soccer video summarizationhough transformlogo-based detectionreplay detectionsoccer event detection
저자
Hossam M. Zawbaa [ Cairo University, Faculty of Computers and Information, Cairo, Egypt ]
Nashwa El-Bendary [ Arab Academy for Science, Technology, and Maritime Transport, Cairo, Egypt ]
Aboul Ella Hassanien [ Cairo University, Faculty of Computers and Information, Cairo, Egypt ]
보안공학연구지원센터(IJMUE) [Science & Engineering Research Support Center, Republic of Korea(IJMUE)]
설립연도
2006
분야
공학>컴퓨터학
소개
1. 보안공학에 대한 각종 조사 및 연구
2. 보안공학에 대한 응용기술 연구 및 발표
3. 보안공학에 관한 각종 학술 발표회 및 전시회 개최
4. 보안공학 기술의 상호 협조 및 정보교환
5. 보안공학에 관한 표준화 사업 및 규격의 제정
6. 보안공학에 관한 산학연 협동의 증진
7. 국제적 학술 교류 및 기술 협력
8. 보안공학에 관한 논문지 발간
9. 기타 본 회 목적 달성에 필요한 사업
간행물
간행물명
International Journal of Multimedia and Ubiquitous Engineering
간기
월간
pISSN
1975-0080
수록기간
2008~2016
등재여부
SCOPUS
십진분류
KDC 505DDC 605
이 권호 내 다른 논문 / International Journal of Multimedia and Ubiquitous Engineering Vol.7 No2