TGNet: A Lightweight Infrared Thermal Image Gesture Recognition Network Based on Knowledge Distillation and Model Pruning

This paper introduces a new method for real-time gesture recognition using infrared thermal images. We propose a lightweight gesture recognition network based on CNN, called TGNet (ThermoGestureNet). TGNet enhances recognition accuracy through a knowledge distillation strategy and improves inference speed by removing redundant convolutional kernel parameters using model pruning techniques. Experimental comparisons on embedded devices with mainstream lightweight networks show that TGNet demonstrates excellent performance in both recognition speed and accuracy.