The growing availability of multimedia data such as video on personal computers and home equipment creates a strong requirement for efficient tools to manipulate this type of data. Automatic summarization is one of these tools, which automatically creates a short version or subset of key-frames which contains as much information as possible as in the original video. Several approaches have been proposed to define and identify what is the most important content in a video. In this paper, we propose a new approach for the automatic creation of summaries for multi-episode videos, such as TV series. In this case, it is necessary to identify similarities and differences among videos (what's common, what's unique, how they differ) in order to find which elements best characterize a particular video with respect to the others. We describe our proposed method, provide the results of its application on a sample set of videos, and suggest a new criterion to evaluate the quality of the summaries that have been created.
Generating summaries of multi-episodes video
ICME 2001, International Conference on Multimedia & Expo, August 22-25, 2001, Tokyo, Japan
Type:
Conférence
City:
Tokyo
Date:
2001-08-22
Department:
Data Science
Eurecom Ref:
694
Copyright:
© 2001 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
See also:
PERMALINK : https://www.eurecom.fr/publication/694
