scholarly journals Perspective and Evolution of Gesture Recognition for Sign Language: A Review

Sensors ◽  
2020 ◽  
Vol 20 (12) ◽  
pp. 3571
Author(s):  
Jesús Galván-Ruiz ◽  
Carlos M. Travieso-González ◽  
Acaymo Tejera-Fettmilch ◽  
Alejandro Pinan-Roescher ◽  
Luis Esteban-Hernández ◽  
...  
Keyword(s):  
Sign Language ◽  
Gesture Recognition ◽  
Good Option ◽  
Motion Sensor ◽  
Leap Motion ◽  
Different Types ◽  
Recognition Systems ◽  
3D Information

This review analyses the different gesture recognition systems through a timeline, showing the different types of technology, and specifying which are the most important features and their achieved recognition rates. At the end of the review, Leap Motion sensor possibilities are described in detail, in order to consider its application on the field of sign language. This device has many positive characteristics that make it a good option for sign language. One of the most important conclusions is the ability of the Leap Motion sensor to provide 3D information from the hands for due identification.

scholarly journals Recognition of American Sign Language Gestures in a Virtual Reality Using Leap Motion

2019 ◽  
Vol 9 (3) ◽  
pp. 445 ◽  
Author(s):  
Aurelijus Vaitkevičius ◽  
Mantas Taroza ◽  
Tomas Blažauskas ◽  
Robertas Damaševičius ◽  
Rytis Maskeliūnas ◽  
...  
Keyword(s):  
Virtual Reality ◽  
American Sign Language ◽  
Sign Language ◽  
Gesture Recognition ◽  
Three Dimensional ◽  
Leap Motion ◽  
American Sign ◽  
3D Space

We perform gesture recognition in a Virtual Reality (VR) environment using dataproduced by the Leap Motion device. Leap Motion generates a virtual three-dimensional (3D) handmodel by recognizing and tracking user‘s hands. From this model, the Leap Motion applicationprogramming interface (API) provides hand and finger locations in the 3D space. We present asystem that is capable of learning gestures by using the data from the Leap Motion device and theHidden Markov classification (HMC) algorithm. We have achieved the gesture recognitionaccuracy (mean ± SD) is 86.1 ± 8.2% and gesture typing speed is 3.09 ± 0.53 words per minute(WPM), when recognizing the gestures of the American Sign Language (ASL).

Development of Robotic Arm Through Hand Gesture Recognition Using Leap Motion Sensor

2020 ◽  
Vol 17 (4) ◽  
pp. 1889-1893
Author(s):  
T. Archana ◽  
Srigitha S. Nath ◽  
S. Praveenkumar
Keyword(s):  
Gesture Recognition ◽  
Control Strategy ◽  
Low Cost ◽  
Hand Gesture Recognition ◽  
Robotic Arm ◽  
Hand Gesture ◽  
Motion Sensor ◽  
Leap Motion ◽  
Control Techniques ◽  
Natural Movement

The objective of this paper has been the development of a prototype of articulated Robotic arm and implementation of a control strategy for gesture recognition through (Leap motion sensor), by means the natural movement of the fore-arm and hand. The series of advances relative to the control techniques have caused that the robotics it has also introduced as an educational and complement in obligatory basic teachings. To develop and to control Robotic elements locally or remotely, it has always proven to be a clear example of additional motivation. The prototype developed has exceeded the initial expectations and at low cost.

A Comparison of Hardware Based Approaches for Sign Language Gesture Recognition Systems

2019 ◽  
Author(s):  
Uzma Farooq ◽  
Ayesha Asmat ◽  
Mohd Shafry Bin Moh Rahim ◽  
Nabeel Sabir Khan ◽  
Adnan Abid
Keyword(s):  
Sign Language ◽  
Gesture Recognition ◽  
Recognition Systems

Numeral Gesture Recognition Using Leap Motion Sensor

2015 ◽  
Author(s):  
Jayash Kumar Sharma ◽  
Rajeev Gupta ◽  
Vinay Kumar Pathak
Keyword(s):  
Gesture Recognition ◽  
Motion Sensor ◽  
Leap Motion
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