Hand Gesture Detection and Its Application to Virtual Reality Systems

2019 ◽  
pp. 499-504
Author(s):  
M. Fikret Ercan ◽  
Allen Qiankun Liu
Keyword(s):  
Virtual Reality ◽  
Hand Gesture ◽  
Hand Gesture Detection

scholarly journals Face Authenticated Hand Gesture Based Human Computer Interaction for Desktops

2020 ◽  
Vol 20 (4) ◽  
pp. 74-89
Author(s):  
Venkat Mukthineni ◽  
Rahul Mukthineni ◽  
Onkar Sharma ◽  
Swathi Jamjala Narayanan
Keyword(s):  
Virtual Reality ◽  
Augmented Reality ◽  
Human Computer Interaction ◽  
Recognition System ◽  
Hand Gesture ◽  
Gesture Control ◽  
Specialized Equipment ◽  
Hand Gesture Detection ◽  
Detection And Recognition ◽  
Computer Interaction

AbstractHand gesture detection and recognition is a cutting-edge technology that is getting progressively applicable in several applications, including the recent trends namely Virtual Reality and Augmented Reality. It is a key part of Human-Computer Interaction which gives an approach to two-way interaction between the computer and the user. Currently, this technology is limited to expensive and highly specialized equipment and gadgets such as Kinect and the Oculus Rift. In this paper, various technologies and methodologies of implementing a gesture detection and recognition system are discussed. The paper also includes the implementation of a face recognition module using the Viola-Jones Algorithm for authentication of the system followed by hand gesture recognition using CNN to perform basic operations on the laptop. Any type of user can use gesture control as an alternative and interesting way to control their laptop. Furthermore, this can be used as a prototype for future implementations in the field of virtual reality as well as augmented reality.

scholarly journals HAND GESTURE DETECTION USING SEGMENTATION

2021 ◽  
Vol 9 (3) ◽  
Author(s):  
Nishu Sethi ◽  
Shivangi Kaushal ◽  
Neha Bhateja
Keyword(s):  
Hand Gesture ◽  
Hand Gesture Detection

scholarly journals Hand Gesture-Based Virtual Reality Training Simulator for Collaboration Rescue of a Railway Accident

2019 ◽  
Vol 31 (6) ◽  
pp. 577-588
Author(s):  
Jianxi Xu ◽  
Zhao Tang ◽  
Huiwen Zhao ◽  
Jianjun Zhang
Keyword(s):  
Virtual Reality ◽  
Human Computer Interaction ◽  
Safety Training ◽  
Hand Gesture ◽  
Virtual Reality Training ◽  
Training Simulator ◽  
Complex Interactions ◽  
Innovative Tool ◽  
User Experiment ◽  
Firsthand Experience

Abstract Training simulator is an efficient and innovative tool to help users learn professional skills due to its convenience and safety. However, complex human–computer interaction is one of the main disadvantages that limit its effectiveness in safety training, especially for the rescue of a railway accident that requires collaborations. Through designing a set of task-specific hand gestures, we developed a training simulator for the recovery of a railway accident that helps the rescuers learn and practice rescue skills in a life-like environment and gain the firsthand experience. To test the validity of our training simulator, a user experiment is designed to compare it with the controller-based simulator in a between-groups study with 51 participants, focusing on different aspects of effectiveness. The results demonstrate that the hand gesture-based controller can be more efficient and usable to deal with complex interactions than the traditional hand-held controller.

Human hand gesture detection based on EMG signal using ANN

2014 ◽  
Author(s):  
Md. Mehedi Hasan ◽  
Arifur Rahaman ◽  
Md. Faisal Shuvo ◽  
Md. Abu Saleh Ovi ◽  
Md. Mostafizur Rahman
Keyword(s):  
Hand Gesture ◽  
Human Hand ◽  
Emg Signal ◽  
Hand Gesture Detection

Touchless capacitive sensor for hand gesture detection

2011 ◽  
Author(s):  
Fatemeh Aezinia ◽  
YiFan Wang ◽  
Behraad Bahreyni
Keyword(s):  
Capacitive Sensor ◽  
Hand Gesture ◽  
Hand Gesture Detection

scholarly journals DeepHandsVR: Hand Interface Using Deep Learning in Immersive Virtual Reality

Electronics ◽  
2020 ◽  
Vol 9 (11) ◽  
pp. 1863 ◽  
Author(s):  
Taeseok Kang ◽  
Minsu Chae ◽  
Eunbin Seo ◽  
Mingyu Kim ◽  
Jinmo Kim
Keyword(s):  
Virtual Reality ◽  
Deep Learning ◽  
User Satisfaction ◽  
Simple Structure ◽  
Hand Gesture ◽  
Immersive Virtual Reality ◽  
Positive Effects ◽  
Virtual Hand ◽  
Sense Of Presence ◽  
Deep Learning Model

This paper proposes a hand interface through a novel deep learning that provides easy and realistic interactions with hands in immersive virtual reality. The proposed interface is designed to provide a real-to-virtual direct hand interface using a controller to map a real hand gesture to a virtual hand in an easy and simple structure. In addition, a gesture-to-action interface that expresses the process of gesture to action in real-time without the necessity of a graphical user interface (GUI) used in existing interactive applications is proposed. This interface uses the method of applying image classification training process of capturing a 3D virtual hand gesture model as a 2D image using a deep learning model, convolutional neural network (CNN). The key objective of this process is to provide users with intuitive and realistic interactions that feature convenient operation in immersive virtual reality. To achieve this, an application that can compare and analyze the proposed interface and the existing GUI was developed. Next, a survey experiment was conducted to statistically analyze and evaluate the positive effects on the sense of presence through user satisfaction with the interface experience.

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