Host: The Japan Society of Mechanical Engineers
Name : [in Japanese]
Date : March 14, 2018 - March 15, 2018
The crowd behavior recognition system is a subsystem of a distributed cooperative dynamic evacuation guidance system, and it detects and predicts crowd flow and abnormality occurrence by using machine learning method such as deep learning with visual and depth information obtained by RGB-D camera. The distributed cooperative dynamic evacuation guidance system aims to suggest evacuation routes at extensive evacuation situations by autonomously cooperation among plural sensors and evacuation guiding devices. In this paper, an edge device is employed for crowd behavior recognition and anomaly detection under a concept of the edge computing. The system which has been considered so far is implemented on the JETSON TX1 which is employed as the edge device. Some results of evaluation of that implementation are reported.
