A unified approach to the generation of semantic cues for sports video annotation

Authors:
K. Messer;W. J. Christmas;E. Jaser;J. Kittler;B. Levienaise-Obadia;D. Koubaroulis
Affiliations:
Centre for Vision, Speech and Signal Processing, University of Surrey, Guildford GU2 7XH, UK;Centre for Vision, Speech and Signal Processing, University of Surrey, Guildford GU2 7XH, UK;Centre for Vision, Speech and Signal Processing, University of Surrey, Guildford GU2 7XH, UK;Centre for Vision, Speech and Signal Processing, University of Surrey, Guildford GU2 7XH, UK;Vision Technologies Laboratory, Sarnoff Corporation, 201 Washington Road, CN 5300, Princeton, NJ;Silverbrook Research Pty Ltd., 393 Darling St., Balmain 2041, NSW, Australia
Venue:
Signal Processing - Special section on content-based image and video retrieval
Year:
2005

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Abstract

The use of video and audio features for automated annotation of audio-visual data is becoming widespread. A major limitation of many of the current methods is that the stored indexing features are too low-level they relate directly to properties of the data. In this work we apply a further stage of processing that associates the feature measurements with real-world objects or events. The outputs, which we call "cues", are combined to enable us to compute directly the probability of the object being present in the scene. An additional advantage of this approach is that the cues from different types of features are presented in a homogeneous way.