Related papers: Hand Gesture Recognition for Collaborative Robots …
Human-robot collaboration has benefited users with higher efficiency towards interactive tasks. Nevertheless, most collaborative schemes rely on complicated human-machine interfaces, which might lack the requisite intuitiveness compared…
Hand gesture is one of the most important means of touchless communication between human and machines. There is a great interest for commanding electronic equipment in surgery rooms by hand gesture for reducing the time of surgery and the…
This paper proposes a novel approach to recognizing dynamic hand gestures facilitating seamless interaction between humans and robots. Here, each robot manipulator task is assigned a specific gesture. There may be several such tasks, hence,…
We propose a set of communicative gestures and develop a gesture recognition system with the aim of facilitating more intuitive Human-Robot Interaction (HRI) through gestures. First, we propose a set of commands commonly used for…
Online recognition of gestures is critical for intuitive human-robot interaction (HRI) and further push collaborative robotics into the market, making robots accessible to more people. The problem is that it is difficult to achieve accurate…
Human-to-Robot handovers are useful for many Human-Robot Interaction scenarios. It is important to recognize when a human intends to initiate handovers, so that the robot does not try to take objects from humans when a handover is not…
In this paper, we present an efficient method to incrementally learn to classify static hand gestures. This method allows users to teach a robot to recognize new symbols in an incremental manner. Contrary to other works which use special…
In this work, we propose a gesture based language to allow humans to interact with robots using their body in a natural way. We have created a new gesture detection model using neural networks and a custom dataset of humans performing a set…
In recent years robots have become an important part of our day-to-day lives with various applications. Human-robot interaction creates a positive impact in the field of robotics to interact and communicate with the robots. Gesture…
As robots become increasingly prevalent in both homes and industrial settings, the demand for intuitive and efficient human-machine interaction continues to rise. Gesture recognition offers an intuitive control method that does not require…
Dynamic hand gestures play a crucial role in conveying nonverbal information for Human-Robot Interaction (HRI), eliminating the need for complex interfaces. Current models for dynamic gesture recognition suffer from limitations in effective…
Gesture recognition is a very essential technology for many wearable devices. While previous algorithms are mostly based on statistical methods including the hidden Markov model, we develop two dynamic hand gesture recognition techniques…
New and more natural human-robot interfaces are of crucial interest to the evolution of robotics. This paper addresses continuous and real-time hand gesture spotting, i.e., gesture segmentation plus gesture recognition. Gesture patterns are…
Hand gestures recognition (HGR) is one of the main areas of research for the engineers, scientists and bioinformatics. HGR is the natural way of Human Machine interaction and today many researchers in the academia and industry are working…
The focus of this paper is dynamic gesture recognition in the context of the interaction between humans and machines. We propose a model consisting of two sub-networks, a transformer and an ordered-neuron long-short-term-memory (ON-LSTM)…
We develop Few-Shot Learning models trained to recognize five or ten different dynamic hand gestures, respectively, which are arbitrarily interchangeable by providing the model with one, two, or five examples per hand gesture. All models…
Automated hand gesture recognition has been a focus of the AI community for decades. Traditionally, work in this domain revolved largely around scenarios assuming the availability of the flow of images of the user hands. This has partly…
Due to the universal non-verbal natural communication approach that allows for effective communication between humans, gesture recognition technology has been steadily developing over the previous few decades. Many different strategies have…
The dynamic hand gesture recognition task has seen studies on various unimodal and multimodal methods. Previously, researchers have explored depth and 2D-skeleton-based multimodal fusion CRNNs (Convolutional Recurrent Neural Networks) but…
Hand gestures form an intuitive means of interaction in Mixed Reality (MR) applications. However, accurate gesture recognition can be achieved only through state-of-the-art deep learning models or with the use of expensive sensors. Despite…