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Real Time Virtual Human Hand Using Leap Motion Controller

Satheeshkumar R., Arivoli R.

International Journal of Electronics and Telecommunications

2021

Vol. 67, No. 3

471--476

The research of robotics needs a good and accurate control. The proposed concept is touch less and non-verbal communication with the use of leap motion controller. The concept has two major parts: first part is “device perceive hand finger moments and send signal”, second part is robotic hand interfaced with PIC microcontroller which receives signal and controls robotic hand. The paper aims to link virtual environment with real time environment. The virtual environment is consisting of leap motion controller and laptop, real time environment is consisting of microcontroller and robotic arm. In real time environment parodist is converts into virtual environment.

Recognition of Sign Language from High Resolution Images Using Adaptive Feature Extraction and Classification

Csóka Filip, Polec Jaroslav, Csóka Tibor, Kačur Juraj

International Journal of Electronics and Telecommunications

2019

Vol. 65, No. 2

303--308

A variety of algorithms allows gesture recognition in video sequences. Alleviating the need for interpreters is of interest to hearing impaired people, since it allows a great degree of self-sufficiency in communicating their intent to the non-sign language speakers without the need for interpreters. State-of-the-art in currently used algorithms in this domain is capable of either real-time recognition of sign language in low resolution videos or non-real-time recognition in high-resolution videos. This paper proposes a novel approach to real-time recognition of fingerspelling alphabet letters of American Sign Language (ASL) in ultra-high-resolution (UHD) video sequences. The proposed approach is based on adaptive Laplacian of Gaussian (LoG) filtering with local extrema detection using Features from Accelerated Segment Test (FAST) algorithm classified by a Convolutional Neural Network (CNN). The recognition rate of our algorithm was verified on real-life data.