Authors:
Sota Kato
and
Kazuhiro Hotta
Affiliation:
Meijo University, 1-501 Shiogamaguchi, Tempaku-ku, Nagoya 468-8502, Japan
Keyword(s):
Habit Detection, Video Classification, Pitching Classification, V-Net, Grad-CAM.
Abstract:
In this paper, we propose a method that is classified pitching motions using deep learning and detected the habits of pitching. In image classification, there is a method called Grad-CAM to visualize the location related to classification. However, it is difficult to apply the Grad-CAM to conventional video classification methods using 3D-Convolution. To solve this problem, we propose a video classification method based on V-Net. By reconstructing input video, it is possible to visualize the frame and location related to classification result based on Grad-CAM. In addition, we improved the classification accuracy in comparison with conventional methods using 3D-Convolution and reconstruction. From experimental results, we confirmed the effectiveness of our method.