Semantic based adaptive movie summarisation

Authors:
Reede Ren;Hemant Misra;Joemon M. Jose
Affiliations:
Information Retrieval Group, University of Glasgow, Glasgow, UK;Information Retrieval Group, University of Glasgow, Glasgow, UK;Information Retrieval Group, University of Glasgow, Glasgow, UK
Venue:
MMM'10 Proceedings of the 16th international conference on Advances in Multimedia Modeling
Year:
2010

Citing 12
Cited 0

Determining computable scenes in films and their structures using audio-visual memory models

MULTIMEDIA '00 Proceedings of the eighth ACM international conference on Multimedia
A statistical model for domain-independent text segmentation

ACL '01 Proceedings of the 39th Annual Meeting on Association for Computational Linguistics
A framework for aligning and indexing movies with their script

ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 2
Automatically selecting shots for action movie trailers

MIR '06 Proceedings of the 8th ACM international workshop on Multimedia information retrieval
Automated production of TV program trailer using electronic program guide

Proceedings of the 6th ACM international conference on Image and video retrieval
Attention-based video summarisation in rushes collection

Proceedings of the international workshop on TRECVID video summarization
Video summarisation: A conceptual framework and survey of the state of the art

Journal of Visual Communication and Image Representation
The trecvid 2008 BBC rushes summarization evaluation

TVS '08 Proceedings of the 2nd ACM TRECVid Video Summarization Workshop
Using LDA to detect semantically incoherent documents

CoNLL '08 Proceedings of the Twelfth Conference on Computational Natural Language Learning
Text segmentation via topic modeling: an analytical study

Proceedings of the 18th ACM conference on Information and knowledge management
Multiband Modulation Energy Tracking for Noisy Speech Detection

IEEE Transactions on Audio, Speech, and Language Processing
Affective video content representation and modeling

IEEE Transactions on Multimedia

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper proposes a framework for automatic video summarization by exploiting internal and external textual descriptions. The web knowledge base Wikipedia is used as a middle media layer, which bridges the gap between general user descriptions and exact film subtitles. Latent Dirichlet Allocation (LDA) detects as well as matches the distribution of content topics in Wikipedia items and movie subtitles. A saliency based summarization system then selects perceptually attractive segments from each content topic for summary composition. The evaluation collection consists of six English movies and a high topic coverage is shown over official trails from the Internet Movie Database.