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WP2: Evaluation, Integration and Standards
WP3: Visual Content Indexing
WP4: Content Description for Audio, Speech and Text
WP5: Multimodal Processing and Interaction
WP6: Machine Learning and Computation Applied to Multimedia
WP7: Dissemination towards Industry

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Home arrow News arrow Previous news arrow Visual Active Memory Application
Visual Active Memory Application

Understanding and Annotating Tennis

The research sets out to explore how an active memory system, operating at several different semantic levels, might lead to a degree of machine understanding when applied to specific scenarios. At present the system (see below) will automatically analyse a tennis video to the extent that it can identify the outcome of each tennis serve and point played, with reasonable accuracy (84% at 22/7/2005). 

The system is in two parts: a short-term and a long-term memory. The short-term memory analyses the video in a bottom-up fashion, making available relevant results to the long-term memory, and "forgetting" the rest. The long-term memory stores only the information that might be useful in the long term, and provides a graphical interface for browsing this information in a top-down fashion.


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