@inproceedings{e546c741733c40f5bb1afd4e9c87115e,
title = "Using Gabor filter in 3D convolutional neural networks for human action recognition",
abstract = "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.",
keywords = "3D CNNs, Action recognition, Gabor filter",
author = "Jiakun Li and Tian Wang and Yi Zhou and Ziyu Wang and Hichem Snoussi",
note = "Publisher Copyright: {\textcopyright} 2017 Technical Committee on Control Theory, CAA.; 36th Chinese Control Conference, CCC 2017 ; Conference date: 26-07-2017 Through 28-07-2017",
year = "2017",
month = sep,
day = "7",
doi = "10.23919/ChiCC.2017.8029134",
language = "英语",
series = "Chinese Control Conference, CCC",
publisher = "IEEE Computer Society",
pages = "11139--11144",
editor = "Tao Liu and Qianchuan Zhao",
booktitle = "Proceedings of the 36th Chinese Control Conference, CCC 2017",
address = "美国",
}