Recognition of Dynamic Hand Gestures in Long Distance using a Web-Camera for Robot Guidance

TL;DR

This paper presents a novel model combining SlowFast and Transformer architectures to recognize dynamic hand gestures from a long distance of up to 20 meters, enhancing robot communication capabilities.

Contribution

The work introduces a new model that effectively recognizes long-distance dynamic gestures, surpassing existing models in recognition range and accuracy.

Findings

Effective recognition at distances up to 20 meters

Superior performance of SFT over existing models

Enhanced robot communication through long-distance gesture recognition

Abstract

Dynamic gestures enable the transfer of directive information to a robot. Moreover, the ability of a robot to recognize them from a long distance makes communication more effective and practical. However, current state-of-the-art models for dynamic gestures exhibit limitations in recognition distance, typically achieving effective performance only within a few meters. In this work, we propose a model for recognizing dynamic gestures from a long distance of up to 20 meters. The model integrates the SlowFast and Transformer architectures (SFT) to effectively process and classify complex gesture sequences captured in video frames. SFT demonstrates superior performance over existing models.