Earticle

초록

영어

In this paper, we present a practical identification approach of video fragment for digital video files. Before analyzing the video content, we must decode it based on its encoding format first. In order to effectively identify the format of a fragment, a format classification is performed before the format identification. The methods of format classification and identification are discriminative subspace clustering (DiSC) and the K-nearest neighbor (KNN).Because of losing the meta-information, we add a maximum similar header (MSH) to the front of the fragment to recover the video content. We adopt a simple key frame detection method using standard deviation and mean value. Motion vectors of macro blocks are utilized to classify the video features for effectively identifying the video. Several edges of frames are accumulated and compose a video feature. The experimental results show the evaluations of the video format classification and identification, fragment recovery, and content identification.

목차

Abstract
 1. Introduction
 2. Video Format Classification and Identification
  2.1. Format Feature Extraction
  2.2. Format Classification Using DiSC
  2.3. Format Identification Using KNN
 3. Video Fragment Recovery
 4. Video Classification and Identification
 5. Performance Evaluation
 6. Conclusion
 Acknowledgments
 References

키워드

저자

• Xun Jin [ Dept. of Copyright Protection, Dept. of Content and Copyright Sangmyung University, Seoul, Korea, Sangmyung University, Seoul, Korea ]
• Jongweon Kim [ Dept. of Copyright Protection, Dept. of Content and Copyright Sangmyung University, Seoul, Korea, Sangmyung University, Seoul, Korea ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Multimedia and Ubiquitous Engineering

• 간기

  월간

• pISSN

  1975-0080

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605