Share Email Print

Proceedings Paper

Comparison of automatic video segmentation algorithms
Author(s): Apostolos Dailianas; Robert B. Allen; Paul England
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

While several methods of automatic video segmentation for the identification of shot transitions have been proposed, they have not been systematically compared. We examine several segmentation techniques across different types of videos. Each of these techniques defines a measure of dissimilarity between successive frames which is then compared to a threshold. Dissimilarity values exceeding the threshold identify shot transitions. The techniques are compared in terms of the percentage of correct and false identifications for various thresholds, their sensitivity to the threshold value, their performance across different types of video, their ability to identify complicated transition effects, and their requirements for computational resources. Finally, the definition of a priori set of values for the threshold parameter is also examined. Most techniques can identify over 90% of the real shot transitions but have a high percentage of false positives. Reducing the false positives was a major challenge, and we introduced a local filtering technique that was fairly effective.

Paper Details

Date Published: 3 January 1996
PDF: 15 pages
Proc. SPIE 2615, Integration Issues in Large Commercial Media Delivery Systems, (3 January 1996); doi: 10.1117/12.229193
Show Author Affiliations
Apostolos Dailianas, Columbia Univ. (United States)
Robert B. Allen, Bell Communications Research (United States)
Paul England, Bell Communications Research (United States)

Published in SPIE Proceedings Vol. 2615:
Integration Issues in Large Commercial Media Delivery Systems
Andrew G. Tescher; V. Michael Bove, Editor(s)

© SPIE. Terms of Use
Back to Top