Computer Science Department
School of Computer Science, Carnegie Mellon University
MMSS: Graph-Based Multi-modal Story-oriented
Video Summarization and Retrieval
Jia-Yu Pan, Hyungjeong Yang, Christos Faloutsos
Keywords: Story summarization, multi-modal video summarization,
video retrieval, random walk, graph application
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 correlations between information of different
modalities and gives meaningful story-oriented news video summaries.
MMSS can also be applied for video retrieval, achieving
performance that matches the best traditional retrieval techniques
(OKAPI and LSI), with no fine-tuned heuristics such as tf/idf.