MMSS: Multi-Modal Story-Oriented Video Summarization

Authors:
Jia-Yu Pan;Hyungjeong Yang;Christos Faloutsos
Affiliations:
Carnegie Mellon University;Carnegie Mellon University;Carnegie Mellon University
Venue:
ICDM '04 Proceedings of the Fourth IEEE International Conference on Data Mining
Year:
2004

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Abstract

We propose multi-modal story-oriented video summarization (MMSS) which, unlike previous works that use fine-tuned, domain-specific heuristics, provides a domain-independent, graph-based framework. MMSS uncovers correlation between information of different modalities which gives meaningful story-oriented news video summaries. MMSS can also be applied for video retrieval, giving performance that matches the best traditional retrieval techniques (OKAPI and LSI), with no fine-tuned heuristics such as tf/idf.