Automatic key-frames extraction to represent a video

Author

Congyan, Lang ; De, Xu ; Wengang, Cheng ; Songhe, Feng

Author_Institution

Sch. of Comput. Sci. & Information Technol., Beijing Jiaotong Univ., China

Volume

1

fYear

2004

fDate

31 Aug.-4 Sept. 2004

Firstpage

741

Abstract

An efficient video content representation using automatic key-frames extraction is presented in this paper. The proposed video-content representation provides the capability of the more efficient browsing digital video sequences. Firstly, each video sequence is partitioned into shots by applying a shot-cut detection algorithm. We construct multidimensional shot-level feature vector by fusing audio and visual information to describe the average frame properties of the shot. Secondly, shot selection is accomplished by clustering similar shots so that shots of similar content are gathered together. While for a given shot, key frames are extracted based on maximizing Kullback-Leibler divergence criterion for locating a key-frames set. An experimental system has been built up. Experiments verify the effectiveness of the proposed approach.

Keywords

feature extraction; image representation; image sequences; video signal processing; automatic key-frame extraction; digital video sequence; efficient browsing; efficient video content representation; maximizing Kullback-Leibler divergence criterion; multidimensional shot-level feature vector; shot selection; shot-cut detection algorithm; Algorithm design and analysis; Clustering algorithms; Data mining; Detection algorithms; Entropy; Feature extraction; Information theory; Partitioning algorithms; Random variables; Video sequences;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing, 2004. Proceedings. ICSP '04. 2004 7th International Conference on

Print_ISBN

0-7803-8406-7

Type

conf

DOI

10.1109/ICOSP.2004.1452769

Filename

1452769