20 papers · ranked by Valyu relevance
Mais Yasen, Shaidah Jusoh, Luciano Fadiga
Background With the development of today’s technology, and as humans tend to naturally use hand gestures in their communication process to clarify their intentions, hand gesture recognition is considered to be an important part of Human Computer Interaction (HCI), which gives computers the ability of capturing and…
Yuting Meng, Haibo Jiang, Nengquan Duan, Haijun Wen + 1 more
Hand gesture recognition plays a significant role in human-to-human and human-to-machine interactions. Currently, most hand gesture detection methods rely on fixed hand gesture recognition. However, with the diversity and variability of hand gestures in daily life, this paper proposes a registerable hand gesture…
Fahmid Al Farid, Noramiza Hashim, Junaidi Abdullah, Md Roman Bhuiyan + 5 more
'Wan Noor Shahida Mohd Isa' 'Jia Uddin' 'Mohammad Ahsanul Haque' 'Mohd Nizam Husen' 'Mohamed Daoudi'] Researchers have recently focused their attention on vision-based hand gesture recognition. However, due to several constraints, achieving an effective vision-driven hand gesture recognition system in real time has…
Diana Alejandra Contreras Alejo, Francisco Javier Gallegos Funes
A continuous path performed by the hand in a period of time is considered for the purpose of gesture recognition. Dynamic gestures recognition is a complex topic since it spans from the conventional method of separating the hand from surrounding environment to searching for the fingers and palm. This paper proposes a…
Jagdish Lal Raheja, Ayush Singhal, Anishkha Chaudhary
These days mobile devices like phones or tablets are very common among people of all age. They are connected with network and provide seamless communications through internet or cellular services. These devices can be a big help for the people who are not able to communicatie properly and even in emergency conditions.…
Huihui Wang, Bo Ru, Xin Miao, Qin Gao + 5 more
'Sen Qiu' 'Bowen Ji' 'Wei Gao'] Gesture recognition has found widespread applications in various fields, such as virtual reality, medical diagnosis, and robot interaction. The existing mainstream gesture-recognition methods are primarily divided into two categories: inertial-sensor-based and camera-vision-based…
Neha Baranwal, V. Sharma
Skeleton based recognition systems are gaining popularity and machine learning models focusing on points/joints in a skeleton have proved to be computationally effective and application in many areas like Robotics. It is easy to track points and thereby preserving spatial and temporal information, which plays an…
Richy Yun, Richard Csaky, Debadatta Dash, Isabel Gerrard + 6 more
The progression of human-computer interfaces into immersive and touchless realities requires new ways of interacting with machines that are correspondingly intuitive and seamless. Among these are gesture-based systems that use natural hand movements to interact with and control digital devices. Today, these systems are…
Gautham Krishna G, Karthik Subramanian Nathan, Yogesh Kumar B, Ankith A Prabhu + 2 more
'Ankith A Prabhu' 'Ajay Kannan' 'Vineeth Vijayaraghavan'] Abstract—Human Computer Interaction facilitates intelligent communication between humans and computers, in which gesture recognition plays a prominent role. This paper proposes a machine learning system to identify dynamic gestures using triaxial acceleration…
Kshitij Deshpande, Varad Mashalkar, Kaustubh Mhaisekar, Amaan Naikwadi + 1 more
'Amaan Naikwadi' 'Archana Ghotkar'] Abstract—In recent years, there has been a considerable amount of research in the Gesture Recognition domain, mainly owing to the technological advancements in Computer Vision. Various new applications have been conceptualised and developed in this field. This paper discusses the…
Joyeeta Singha, Karen Das
In this paper, we have proposed a system based on K-L Transform to recognize different hand gestures. The system consists of five steps: skin filtering, palm cropping, edge detection, feature extraction, and classification. Firstly the hand is detected using skin filtering and palm cropping was performed to extract out…
Sajjad Hussain, Khizer Saeed, Almas Baimagambetov, Shanay Rab + 1 more
Enhanced Human-Robot Interaction: A Comprehensive Review Authors: ['Sajjad Hussain' 'Khizer Saeed' 'Almas Baimagambetov' 'Shanay Rab' 'Mohamad Saad'] 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…
Ethan Eddy, Evan Campbell, Scott Bateman, Erik Scheme
Myoelectric control, the use of electromyogram (EMG) signals generated during muscle contractions to control a system or device, is a promising modality for enabling always-available control of emerging ubiquitous computing applications. However, its widespread use has historically been limited by the need for…
Muhammad Asim Khan, Lan Hong, Sajjad Ahmed
— We propose a new technique for recognition of dumb person hand gesture in real world environment. In this technique, the hand image containing the gesture is preprocessed and then hand region is segmented by convergent the RGB color image to L.a.b color space. Only few statistical features are used to classify the…
Marc Martínez-Camarena, José Oramas, Mario Montagud, Tinne Tuytelaars
'Tinne Tuytelaars'] Abstract Over the years, hand gesture recognition has been mostly addressed considering hand trajectories in isolation. However, in most sign languages, hand gestures are defined on a particular context (body region). We propose a pipeline to perform sign language recognition which models hand…
Beiwei Zhang, Yudong Zhang, Jinliang Liu, Bin Wang + 1 more
Gesture recognition has been studied for decades and still remains an open problem. One important reason is that the features representing those gestures are not sufficient, which may lead to poor performance and weak robustness. Therefore, this work aims at a comprehensive and discriminative feature for hand gesture…
Xuhui Hu, Hong Zeng, Dapeng Chen, Jiahang Zhu + 1 more
In this paper an automated data labeling (ADL) neural network was proposed to streamline dataset collecting for real-time predicting the continuous motion of hand and wrist, these gestures are only decoded from a surface electromyography (sEMG) array of eight channels. Unlike collecting both the bio-signals and hand…
Hernandez Vincent, Suzuki Tomoya, Venture Gentiane
Human Action Recognition (HAR) is an important and difficult topic because of the important variability between tasks repeated several times by a subject and between subjects. This work is motivated by providing time-series signal classification and a robust validation and test approaches. This study proposes to…
Filip Rybansky, Sadegh Rahmaniboldaji, Andrew Gilbert, Frank Guerin + 2 more
Humans recognize everyday actions without conscious effort despite challenges such as poor viewing conditions and visual similarity between actions. Yet the visual features contributing to action recognition remain unclear. To address this, we combined semantic modelling and feature reduction methods to identify…
Elnaz Lashgari, Atabak Pouya, Uri Maoz
Human urges, desires, and intentions manifest themselves in voluntary action. The final stages of such voluntary action are the muscle contractions that bring it about. Electromyography (EMG) signals measure such muscle contractions. Decoding action contents from EMG require advanced methods for detection…