Antonio Tejero-de-Pablos

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Human action recognition applications are greatly benefited from the use of commodity depth sensors that are capable of skeleton tracking. Some of these applications (e.g., customizable gesture interfaces) require learning of new actions at runtime and may not count with many training instances. This paper presents a human action recognition method designed(More)
In this paper we introduce, to the best of our knowledge, the first adaptation of the Fuzzy ARTMAP neural network for its execution on a GPU, together with a self-designed neural network based on ART models called SOON. The full VisTex database, containing 167 texture images, is proved to be classified in a very short time using these GPU-based neural(More)
Automatically generating a summary of sports video poses the challenge of detecting interesting moments, or highlights, of a game. Traditional sports video summarization methods leverage editing conventions of broadcast sports video that facilitate the extraction of high-level semantics. However, usergenerated videos are not edited, and thus traditional(More)
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