A Comprehensive Survey on Hand Gesture Recognition Using Deep Learning for Electronic Device Interaction
Bhupendra Sinha · 2025
This survey presents a comprehensive review of Hand Gesture Recognition (HGR), an essential area within computer vision and pattern recognition. HGR finds applications in domains such as robotics, sign language interpretation, healthcare, gaming, and smart devices. With advances in deep learning, sensors, and cameras, companies are integrating contactless hand gesture features into products especially vital during global events like the COVID-19 pandemic. Although significant progress has been made, developing efficient, reliable, and lightweight models for electronic devices with limited memory and processing capabilities remains a challenge. To address these, researchers have explored tools like special cameras (3D, Microsoft Kinect, Intel RealSense depth cameras), wearable gloves, diverse datasets, and fusion of different neural networks. This study systematically examines HGR applications, common research challenges, dataset characteristics, preprocessing techniques, model architectures, and evaluation metrics It also identifies key research gaps and future directions which serve as a valuable reference for researchers and practitioners in the field.