The application of image processing techniques to achieve
substantial compression in digital video is one of the reasons why computer-supported video processing and digital TV are now becoming commonplace. The encoding formats used for video, such as the MPEG family of standards, have been developed primarily to achieve high compression rates, but now that this has been achieved, effort is being concentrated on other, content-based activities. MPEG-7, for example is a standard intended to support such developments. In the work described here, we are developing and deploying
techniques to support content-based navigation and browsing through digital video (broadcast TV) archives. Fundamental to this is being able to automatically structure video into shots and scenes. In this paper we report our progress on developing a variety of approaches to automatic shot boundary detection in MPEG-1 video, and their evaluation on a large test suite of 8 hours of broadcast TV. Our work to date indicates that different techniques work well for different shot transition types and that a combination of techniques may yield the most accurate segmentation.
[1]
Ramin Zabih,et al.
A feature-based algorithm for detecting and classifying production effects
,
1999,
Multimedia Systems.
[2]
Aidan Totterdell.
An Algorithm for Detecting and Classifying Scene Breaks in MPEG Video Bit Streams
,
1998
.
[3]
Jianxin Zhang,et al.
Mutual Spotting Retrieval between Speech and Video Image Using Self-Organized Network Databases
,
1998,
AMCP.
[4]
Alan F. Smeaton.
Independence of Contributing Retrieval Strategies in Data Fusion for Effective Information Retrieval
,
1998,
BCS-IRSG Annual Colloquium on IR Research.
[5]
William K. Pratt,et al.
Developing Visual Applications: Xil : An Imaging Foundation Library
,
1997
.
[6]
John S. Boreczky,et al.
Comparison of video shot boundary detection techniques
,
1996,
J. Electronic Imaging.
[7]
John F. Canny,et al.
A Computational Approach to Edge Detection
,
1986,
IEEE Transactions on Pattern Analysis and Machine Intelligence.