Gesture Description Agent

Gesture description agents are computational systems designed to interpret human hand gestures for seamless human-robot interaction (HRI) and human-computer interaction (HCI). Current research focuses on developing robust methods for translating raw hand movement data (e.g., from cameras or sensors) into natural language descriptions, which are then used by inference agents to understand user intent and trigger appropriate actions. This involves leveraging deep learning architectures, such as convolutional neural networks (CNNs) and vision transformers (ViTs), often combined with recurrent neural networks (RNNs) to process temporal information in dynamic gestures. The ultimate goal is to create intuitive and natural interfaces that improve accessibility and efficiency in various applications, from controlling robots and smart homes to assisting individuals with disabilities.