The major problem facing video databases is that of content characterization of video clips once the cut boundaries have been determined. The current efforts in this direction are focussed exclusively on the use of pictorial information, thereby neglecting an important supplementary source of content information, i.e. the embedded audio or sound track. The current research in audio processing can be readily applied to create many different video indices for use in Video On Demand (VOD), educational video indexing, sports video characterization, etc. MPEG is an emerging video and audio compression standard with rapidly increasing popularity in multimedia industry. Compressed bit stream processing has gained good recognition among the researchers. We have also demonstrated feature extraction in MPEG compressed video which implements a majority of scene change detection schemes on compressed video. In this paper, we examine the potential of audio information for content characterization by demonstrating the extraction of widely used features in audio processing directly from compressed data stream and their application to video clip classification.
[1]
A. Noll.
Cepstrum pitch determination.
,
1967,
The Journal of the Acoustical Society of America.
[2]
Didier Le Gall,et al.
MPEG: a video compression standard for multimedia applications
,
1991,
CACM.
[3]
J H Wu,et al.
\video Browsing Using Clustoring and Scene Transitions on Compressed Sequence," in Spie/is&t 6 Summary and Future Work Abe, \content Oriented Visual Interface Using Video Icons for Visual Database System,"
,
1996
.
[4]
Stephen W. Smoliar,et al.
Video parsing, retrieval and browsing: an integrated and content-based solution
,
1997,
MULTIMEDIA '95.