DocumentCode
2935710
Title
Can social tagged images aid concept-based video search?
Author
Setz, Arjan T. ; Snoek, Cees G M
Author_Institution
Intell. Syst. Lab. Amsterdam, Univ. of Amsterdam, Amsterdam, Netherlands
fYear
2009
fDate
June 28 2009-July 3 2009
Firstpage
1460
Lastpage
1463
Abstract
This paper seeks to unravel whether commonly available social tagged images can be exploited as a training resource for concept-based video search. Since social tags are known to be ambiguous, overly personalized, and often error prone, we place special emphasis on the role of disambiguation. We present a systematic experimental study that evaluates concept detectors based on social tagged images, and their disambiguated versions, in three application scenarios: within-domain, cross-domain, and together with an interacting user. The results indicate that social tagged images can aid concept-based video search indeed, especially after disambiguation and when used in an interactive video retrieval setting. These results open-up interesting avenues for future research.
Keywords
social networking (online); video retrieval; concept detectors; concept-based video search; interactive video retrieval; social tagged images; Content based retrieval; Detectors; Humans; Image retrieval; Intelligent systems; Labeling; Machine learning; Scalability; Speech; Tagging;
fLanguage
English
Publisher
ieee
Conference_Titel
Multimedia and Expo, 2009. ICME 2009. IEEE International Conference on
Conference_Location
New York, NY
ISSN
1945-7871
Print_ISBN
978-1-4244-4290-4
Electronic_ISBN
1945-7871
Type
conf
DOI
10.1109/ICME.2009.5202778
Filename
5202778
Link To Document