Human Action Recognition Based on 3D Edge Oriented Gradient Histogram of Slide Blocks
نویسندگان
چکیده
In this paper, a new feature called 3D edge oriented gradient histogram of slide blocks is proposed for human action recognition, based on the idea that the slide area of human body edge can be seen as a spatio-temporal silhouette surface when human performing a certain action in video. This feature is processed by defining dense 3D spatio-temporal slide blocks on the spatio-temporal silhouette surface to detect the 3D human action shape. A BOW (Bag of Words) model is used firstly combining sparse coding to represent videos based on the new feature and Random Forests as the classifier. Experiments demonstrate that our new feature can describe the spatio-temporal silhouette surface correctly, accordingly recognize the human action types accurately.
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