DocumentCode
2851368
Title
MMSS: multi-modal story-oriented video summarization
Author
Pan, Jia-Yu ; Yang, Hyungjeong ; Faloutsos, Christos
Author_Institution
Dept. of Comput. Sci., Carnegie Mellon Univ., Pittsburgh, PA, USA
fYear
2004
fDate
1-4 Nov. 2004
Firstpage
491
Lastpage
494
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.
Keywords
graph theory; image retrieval; video signal processing; MMSS; domain-independent graph-based framework; fine-tuned domain-specific heuristics; multi-modal story-oriented video summarization; video retrieval; Broadcasting; Computer science; Content based retrieval; Data mining; Information retrieval; Large scale integration; Libraries; Motion pictures; Multimedia communication; Robustness;
fLanguage
English
Publisher
ieee
Conference_Titel
Data Mining, 2004. ICDM '04. Fourth IEEE International Conference on
Print_ISBN
0-7695-2142-8
Type
conf
DOI
10.1109/ICDM.2004.10033
Filename
1410343
Link To Document