Real Time Hand Gesture Recognition in Industry
William Dumoulin, Nicolas Thiry, Rim Slama · 2021
With the 4th industrial revolution and the increased use of cobots in the industries comes many opportunities for new generation control panels. In this article, we proposed to develop a deep learning model to recognize in real time 10 different gestures that can be used to interact with a cobot. We proposed a new dataset containing gestures that can be used in an industrial context. The videos were taken from a computer webcam and then processed to remove the noise created by the background by isolating the movement of the gray scale images. We proposed to extract the spatio-temporal features by the combination of 3D convolution and LSTM layers. We also proposed a real time method to recognize our gestures, the frames are captured continuously and fed to the model to get a prediction every 2.4 seconds. Our experimental results show for 8 out of 10 gestures, a recognition rate of more than 90%. Furthermore, an interface was created to test our method in real time and to add new classes of gestures to be recognized by our model.