Comparison of Feature Construction Methods for Video Relevance Prediction

Authors:
Pablo Bermejo;Hideo Joho;Joemon M. Jose;Robert Villa
Affiliations:
Computing Systems Dept., Universidad de Castilla-La Mancha, Albacete, Spain;Department of Computing Science, University of Glasgow, UK;Department of Computing Science, University of Glasgow, UK;Department of Computing Science, University of Glasgow, UK
Venue:
MMM '09 Proceedings of the 15th International Multimedia Modeling Conference on Advances in Multimedia Modeling
Year:
2009

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Abstract

Low level features of multimedia content often have limited power to discriminate a document's relevance to a query. This motivated researchers to investigate other types of features. In this paper, we investigated four groups of features: low-level object features, behavioural features, vocabulary features, and window-based vocabulary features, to predict the relevance of shots in video retrieval. Search logs from two user studies formed the basis of our evaluation. The experimental results show that the window-based vocabulary features performed best. The behavioural features also showed a promising result, which is useful when the vocabulary features are not available. We also discuss the performance of classifiers.