Hand Gesture Classification Using Grayscale Thermal Images and Convolutional Neural Network

We propose a convolutional neural network for classifying grayscale images of hand gestures in this paper. We look at ten different hand gestures collected from various people using a thermal camera for classification. The proposed model’s performance in terms of classification accuracy and inference time is then compared to that of other benchmark models. Using extensive results, we show that the proposed model achieves higher classification accuracy while using a smaller model size. In terms of inference time, we show that the proposed model outperforms benchmark models.