2024 Volume 5 Issue 1 Pages 77-83
In recent years, efforts have been made in Japan to create walkable street spaces. In this effort, it is important to investigate and understand the action of users of street spaces. However, performing these tasks manually is burdensome in terms of both time and cost. In this research, we are developing a human action detection technology using deep learning, with the aim of improving work efficiency. In this paper, we developed a model that detects various actions listed in the guidelines prescribed by MLIT using camera images taken of street spaces. Then, we showed that it is possible to quantitatively understand the usage situation of actual street space.
