2D Log-Gabor Wavelet Based Action Recognition

摘要

The frequency response of log-Gahor function matches well the frequency response of primate visual neurons. In this letter, motion-salient regions are extracted based on the 2D log-Gabor wavelet transform of the spatio-temporal form of actions. A supervised classification technique is then used to classify the actions. The proposed method is robust to the irregular segmentation of actors. Moreover, the 2D log-Gabor wavelet permits more corropace, representation of actions than the recent neurobiological models using Gabor wavelet.