Action recognition based on shape features and their correlation

This paper presents an approach for action recognition based on binary silhouette sequences extracted from consecutive frames of a video. It uses shape descriptors and correlation coefficient to represent and match entire sequences, regardless the number of frames. Each set of binary silhouettes corresponds to one action, such as jumping or waving. The paper provides experimental results on the use of the proposed approach and four shape description algorithms, namely the Two-Dimensional Fourier Descriptor, Generic Fourier Descriptor, Point Distance Histogram and UNL-Fourier Descriptor. The results are analysed in terms of the highest classification accuracy and the smallest shape descriptor size.

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Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).