Journal of Visual Communication and Image Representation
Volume 7, Issue 4, December 1996, Pages 345-353
Regular ArticleAbstracting Digital Movies Automatically
References (0)
Cited by (141)
What do you wish to see? A summarization system for movies based on user preferences
2015, Information Processing and ManagementCitation Excerpt :It uses efficient similarity measures and a prioritized linear fusion of different similarity scores for both shot level and scene level personalized movie summarization. Various attempts were made over the past decade to automate the summarization of full length movies (Ellouze, Boujemaa, & Alimi, 2010; Fu et al., 2010; Hermes & Schultz, 2006; Li, Lee, Yeh, & Kuo, 2006; Pfeiffer, Lienhart, Fischer, & Effelsberg, 1996; Sang & Xu, 2010; Shroff, Turaga, & Chellappa, 2010; Tobita, 2010; Tsai et al., 2013; Weng et al., 2009). The VAbstract (Pfeiffer et al., 1996) system extracts scenes with dialogue, high contrast and high motion to construct trailers for feature films.
Speeding up a video summarization approach using GPUs and multicore CPUs
2014, Procedia Computer ScienceQuery-based video summarization with multi-label classification network
2023, Multimedia Tools and ApplicationsAn Enhanced and Efficient approach towards text detection and extracting text in multi-oriented images
2023, 2023 International Conference on Artificial Intelligence and Smart Communication, AISC 2023Video Summarization Overview
2022, arXiv
- *
E-mail: [email protected], Fax: +49-621-292-5745.
Copyright © 1996 Academic Press. All rights reserved.