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Most studies about silhouettes based human action recognition focus on the time domain representation. However, the contour of human body usually shows as a time-varying signal, for which neither the time domain based methods nor the Fourier transform can catch enough information to achieve sufficient classification performance. A fractional Fourier shape descriptor is proposed for silhouette based...
We proposed a framework for human action recognition by learning pose dictionary as the human appearance representation. At first, the shape based pose feature is constructed based on the contour points of the human silhouette and invariant to translation and scaling. After the local pose features are extracted from the original videos, the class-specific dictionaries are learned individually on the...
We present an oriented holistic feature, namely weighted oriented pixel change history(WOPCH), to describe reciprocating motions and differentiate actions similar in appearance for human action recognition. To construct the oriented representation, we incorporate motion information into pixel change history(PCH) image, through splitting the PCH image into several oriented channels according to the...
This paper proposes a novel fast-semi-supervised-FCM algorithm (fsFCM) to fundamentally overcome the critical disadvantages of Pedrycz's semi-supervised-FCM(sFCM) ,i.e., degeneracy to classical FCM and slow convergence, particularly when applied in actual data set. Experimental results demonstrate that fsFCM can outperform sFCM in accuracy, speed and robustness for clustering. Moreover, it shows that...
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