A Gesture Recognition System for Cranes Using Deep Learning with a Self-attention Mechanism
Keigo Watanabe, Maierdan Maimaitimin, Kazuki Yamamoto, Isaku NAGAI · 2022
This research is aimed at recognizing the gesture of a lifting coordinator and automating the operation of a crane by introducing a system with deep learning. This paper first explains the outline of a gesture recognition system, and describes skeletal detection and its accuracy improvement technique. Furthermore, a gesture recognition system is constructed using a 1DCNN, and the recognition accuracy is verified to be improved by introducing a self-attention mechanism.