A Method of Combining Multiple Experts for the Recognition of Unconstrained Handwritten Numerals
IEEE Transactions on Pattern Analysis and Machine Intelligence
A framework for recognizing multi-agent action from visual evidence
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
A region—based image database system using colour and texture
Pattern Recognition Letters - Special issue on pattern recognition in practice VI
Colour Image Retrieval and Object Recognition Using the Multimodal Neighbourhood Signature
ECCV '00 Proceedings of the 6th European Conference on Computer Vision-Part I
A unified approach to the generation of semantic cues for sports video annotation
Signal Processing - Special section on content-based image and video retrieval
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This paper describes an aspect of a developing system named ASSAVID which will provide an automatic and semantic annotation of sports video. This annotation process segments the sports video into semantic categories (e.g. type of sport) and permits the user to formulate queries to retrieve events that are significant to that particular sport (e.g. goal, foul). The system relies upon the concept of "cues" which attach semantic meaning to low-level features computed on the video. In this paper we adopt the multiple classifier system approach to fusing the outputs of multiple cue detectors using Behaviour Knowledge Space fusion. Using this technique, unknown sports video can be classified into the type of sport being played. Experimental results on sports video provided by the BBC demonstrate that this method is working well.