Motion dense sampling and component clustering for action recognition
نویسندگان
چکیده
منابع مشابه
Action recognition by saliency-based dense sampling
Action recognition, aiming to automatically classify actions from a series of observations, has attracted more attention in the computer vision community. The state-of-the-art action recognition methods utilize dense sampled trajectories to build feature representations. However, their performances are limited due to action region clutters and camera motions in real world applications. No matte...
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The most important problem in action recognition is how to represent an action video. The approaches can be roughly divided into four categories: (1) human pose based approaches which utilize human structure information; (2) global action template based approaches which capture appearance and motion information on the whole motion body; (3) local feature based approaches which mainly extract va...
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ژورنال
عنوان ژورنال: Multimedia Tools and Applications
سال: 2014
ISSN: 1380-7501,1573-7721
DOI: 10.1007/s11042-014-2112-1