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Learning temporal causal structures between time series is one of the key tools for analyzing time series data. In many real-world applications, we are confronted with Irregular T...
We describe a mid-level approach for action recognition. From an input video, we extract salient spatio-temporal structures by forming clusters of trajectories that serve as candi...
Successful software maintenance is becoming increasingly critical due to the increasing dependence of our society and economy on software systems. One key problem of software main...
The preservation of temporal dependencies among different media data, such as text, still images, video and audio, and which have simultaneous distributed sources as origin, is an ...
Saul Pomares Hernandez, Luis A. Morales Rosales, J...
In this paper, we address the problem of representing human actions using visual cues for the purpose of learning and recognition. Traditional approaches model actions as space-ti...