Key frame extraction is considered as one of the most critical issues in content-based video retrieval technology (CBVR). In this paper, an efficient key frame extraction algorithm based on unsupervised clustering and compressive sensing is proposed. Firstly, three types of filters with various scales are employed to generate high dimensional feature of each frame in one shot, which will be projected to low dimensional feature by a very sparse random projection matrix that satisfies the condition of Restricted Isometry Property (RIP), and then sub-shot segmentation is conducted by an unsupervised clustering method in order to divide one shot into sub-shot collections, in which each class of clustering represents one sub-shot. Finally, the Bhattacharyya coefficient is used to measure the similarity between frame and class center, the frame with the maximum similarity value is selected as the key frame in each sub-shot. The experimental results demonstrate that the proposed method could extract key frames efficiently and properly.
목차
Abstract 1. Introduction 2. Related Work 2.1. Existing Key Frame Extraction Methods 2.2. Compressive Sensing 2.3. Motivation of the Proposed Algorithm 3. Proposed Algorithm 3.1. High Dimensional Feature Construction 3.2. Low Dimensional Feature Generation 3.3. Sub-Shot Segmentation 3.4. Key Frame Extraction 4. Experiments 5. Conclusion References
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.10 No.11