Using Gabor filter in 3D convolutional neural networks for human action recognition
Jiakun Li, Tian Wang, Yi Zhou, Ziyu Wang, Hichem Snoussi · 2017
Human action recognition is an important topic in the field of computer vision. We use Gabor filter in 3D CNNs models in recognizing action. Convolutional neural networks (CNNs) are a type of deep learning models, which is an efficient recognition model and has a unique superiority in image processing. Three dimension convolutional neural networks can well analyze action from video data. Gabor filter is a special convolution kernel. Its performance in feature extraction is outstanding. We test out model by KTH dataset and achieve a well result.