PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Can Social Tagged Images Aid Concept-Based Video Search?
Arjan T. Setz and Cees G.M. Snoek
In: IEEE International Conference on Multimedia & Expo(2009).

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.

EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Machine Vision
Information Retrieval & Textual Information Access
ID Code:6196
Deposited By:Christof Monz
Deposited On:08 March 2010