@techreport{oai:ipsj.ixsq.nii.ac.jp:00218589,
 author = {Shurong, Chai and Jiaqing, Liu and Tomoko, Tateyama and Lanfen, Lin and Yen-Wei, Chen and Shurong, Chai and Jiaqing, Liu and Tomoko, Tateyama and Lanfen, Lin and Yen-Wei, Chen},
 issue = {19},
 month = {Jun},
 note = {Recently, emotion recognition task has attracted extensive attention in the field of human-computer interaction. With the advancement of Graph Convolutional Networks (GCNs), human gait can be effectively recognized in more complex backgrounds. According to the anatomy of the human body, central torso joints play a key role in GCNs-based human gait recognition systems, instead of the body’s marginal limb joints. As a result, there is a major issue of receptive field imbalance. In this study, we propose a method for perceiving emotions based on the human gait skeleton. We present a novel pseudo node strategy that connects all natural human body joints to alleviate the receptive field imbalance problem. The result of the experiment show that our proposed method outperforms than existing skeleton-based methods., Recently, emotion recognition task has attracted extensive attention in the field of human-computer interaction. With the advancement of Graph Convolutional Networks (GCNs), human gait can be effectively recognized in more complex backgrounds. According to the anatomy of the human body, central torso joints play a key role in GCNs-based human gait recognition systems, instead of the body’s marginal limb joints. As a result, there is a major issue of receptive field imbalance. In this study, we propose a method for perceiving emotions based on the human gait skeleton. We present a novel pseudo node strategy that connects all natural human body joints to alleviate the receptive field imbalance problem. The result of the experiment show that our proposed method outperforms than existing skeleton-based methods.},
 title = {A pseudo node based graph convolution network for emotion perception from gait},
 year = {2022}
}