VirtualBoard: real-time visual gesture recognition for natural human-computer interaction

2004 ◽  
Author(s):  
C. Costanzo ◽  
G. Iannizzotto ◽  
F. La Rosa
Keyword(s):  
Human Computer Interaction ◽  
Real Time ◽  
Gesture Recognition ◽  
Computer Interaction

scholarly journals Real-Time Hand Gesture Spotting and Recognition Using RGB-D Camera and 3D Convolutional Neural Network

2020 ◽  
Vol 10 (2) ◽  
pp. 722 ◽  
Author(s):  
Dinh-Son Tran ◽  
Ngoc-Huynh Ho ◽  
Hyung-Jeong Yang ◽  
Eu-Tteum Baek ◽  
Soo-Hyung Kim ◽  
...  
Keyword(s):  
Neural Network ◽  
Human Computer Interaction ◽  
Real Time ◽  
Gesture Recognition ◽  
Hand Gesture Recognition ◽  
Video Gaming ◽  
Hand Gesture ◽  
Novel Method ◽  
High Level ◽  
Computer Interaction

Using hand gestures is a natural method of interaction between humans and computers. We use gestures to express meaning and thoughts in our everyday conversations. Gesture-based interfaces are used in many applications in a variety of fields, such as smartphones, televisions (TVs), video gaming, and so on. With advancements in technology, hand gesture recognition is becoming an increasingly promising and attractive technique in human–computer interaction. In this paper, we propose a novel method for fingertip detection and hand gesture recognition in real-time using an RGB-D camera and a 3D convolution neural network (3DCNN). This system can accurately and robustly extract fingertip locations and recognize gestures in real-time. We demonstrate the accurateness and robustness of the interface by evaluating hand gesture recognition across a variety of gestures. In addition, we develop a tool to manipulate computer programs to show the possibility of using hand gesture recognition. The experimental results showed that our system has a high level of accuracy of hand gesture recognition. This is thus considered to be a good approach to a gesture-based interface for human–computer interaction by hand in the future.

scholarly journals A Novel Hand Gesture Recognition Based on High-Level Features

2018 ◽  
Vol 15 (02) ◽  
pp. 1750022 ◽  
Author(s):  
Jing Li ◽  
Jianxin Wang ◽  
Zhaojie Ju
Keyword(s):  
Human Computer Interaction ◽  
Real Time ◽  
Gesture Recognition ◽  
Feature Fusion ◽  
Recognition System ◽  
Depth Information ◽  
Static Gesture Recognition ◽  
Time Requirements ◽  
High Level ◽  
Computer Interaction

Gesture recognition plays an important role in human–computer interaction. However, most existing methods are complex and time-consuming, which limit the use of gesture recognition in real-time environments. In this paper, we propose a static gesture recognition system that combines depth information and skeleton data to classify gestures. Through feature fusion, hand digit gestures of 0–9 can be recognized accurately and efficiently. According to the experimental results, the proposed gesture recognition system is effective and robust, which is invariant to complex background, illumination changes, reversal, structural distortion, rotation, etc. We have tested the system both online and offline which proved that our system is satisfactory to real-time requirements, and therefore it can be applied to gesture recognition in real-world human–computer interaction systems.

ZatLab

2015 ◽  
pp. 224-254 ◽  
Author(s):  
André Baltazar ◽  
Luís Gustavo Martins
Keyword(s):  
Human Computer Interaction ◽  
Real Time ◽  
Gesture Recognition ◽  
Computer Programming ◽  
Easy Task ◽  
Artistic Applications ◽  
Computer Interaction

Computer programming is not an easy task, and as with all difficult tasks, it can be faced as tedious, impossible to do, or as a challenge. Therefore, learning to program with a purpose enables that “challenge mindset” and encourages the student to apply himself in overcoming his handicaps and exploring different theories and methods to achieve his goal. This chapter describes the process of programming a framework with the purpose of achieving real time human gesture recognition. Just this is already a good challenge, but the ultimate goal is to enable new ways of Human-Computer Interaction through expressive gestures and to allow a performer the possibility of controlling (with his gestures), in real time, creative artistic events. The chapter starts with a review on human gesture recognition. Then it presents the framework architecture, its main modules, and algorithms. It closes with the description of two artistic applications using the ZatLab framework.

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