Static Gesture

Static gesture recognition focuses on automatically identifying non-moving hand poses, primarily using radar sensors (UWB and mmWave) to overcome limitations of camera-based systems in various lighting conditions and privacy concerns. Research heavily employs convolutional neural networks (CNNs), sometimes augmented with techniques like sterile training to improve accuracy on limited datasets, and explores alternative architectures such as MobileNet and LSTM-CNNs for different applications. This field is significant for advancing human-computer interaction (HCI), particularly in virtual and augmented reality, robotics (human-robot interaction), and accessibility technologies, offering more intuitive and robust interfaces.