A Hybrid Approach to Improving Semantic Extraction of News Video

Abstract

In this paper we describe a hybrid approach to improving semantic extraction from news video. Experiments show the value of careful parameter tuning, exploiting multiple feature sets and multilingual linguistic resources, applying text retrieval approaches for image features, and establishing synergy between multiple concepts through undirected graphical models. No single approach provides a consistently better result for every concept detection, which suggests that extracting video semantics should exploit multiple resources and techniques rather than a single approach.

DOI: 10.1109/ICSC.2007.68

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Cite this paper

@article{Hauptmann2007AHA, title={A Hybrid Approach to Improving Semantic Extraction of News Video}, author={Alexander G. Hauptmann and Ming-yu Chen and Michael G. Christel and Wei-Hao Lin and Jun Yang}, journal={International Conference on Semantic Computing (ICSC 2007)}, year={2007}, pages={79-86} }