Human action recognition has been one of the
most challenging topics in computer vision during the last
decade. This paper presents a novel approach for recognizing
view independent human actions based on analysis of Fourier
transform and Radon transform of self similarity matrix of
features obtained from the action. The proposed feature
descriptor is extracted from human point cloud over the time and
is based on the key idea that some parts of human body which
have a longer distance from the body center are more
discriminative for human action recognition purposes. The
effectiveness of the proposed method is demonstrated with the
experiments on i3DPost dataset.