You can find below our recently accepted work at IEEE Access, entitled “Survey on Hand Gesture Recognition from Visual Input” and authored by M. Linardakis, I. Varlamis and G. Th. Papadopoulos.
Link: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11098825
The study was funded by the European RnD projects TRIFFID Project and TORNADO EU project
Hand gesture recognition has become an important research area, driven by the demand for human-computer interaction in fields such as sign language recognition, virtual and augmented reality, and robotics.
This study provides a comprehensive survey of the field, focusing on:
- The latest advancements in hand gesture and 3D hand pose recognition from various types of camera input data including RGB images, depth images, and videos from monocular or multiview cameras, examining the differing methodological requirements of each approach.
- An overview of widely used datasets, detailing their main characteristics and application domains.
- Οpen challenges such as achieving robust recognition in real-world environments, handling occlusions, ensuring generalization across diverse users, and addressing computational efficiency for real-time applications are highlighted to guide future research directions.
