Evaluation of Gesture Description Language in the role of touchless interface for virtual reality environment

Abstract

The main novelty presented in this paper is application and evaluation our Gesture Description Language (GDL) classifier in the role of touchless interface for virtual reality (VR) environment. In our VR system whole interaction is done by gestures and body movements analysis (so called natural user interface). For our needs we have adapted semi-realistic VR system (block engine). We have tested different aspects of proposed interface on a group of 26 persons with wide range of age (from 5 years to 40+) and both sexes. The results we obtained prove that GDL can be successfully applied in systems that require real time action recognition especially educational software games that aim at increasing the students' motivation and engagement while they learn. Streszczenie. W tym artykule autorzy prezentują zastosowanie klasyfikatora o nazwie Język Opisu Gestów (GDL) w roli bezdotykowego interfejsu systemu wirtualnej rzeczywistości. Całość interakcji z zaprezentowanym w tej pracy systemem odbywa się poprzez rozpoznanie i analizę ruchu użytkownika (jest to tak zwany interfejs naturalny). Klasyfikator GDL został przetestowany w pseudo-realistycznym, wirtualnym środowisku, na grupie 26 osób obu płci w przedziale wiekowym od 5 do 40+ lat. Otrzymane rezultaty dowodzą, że zaproponowane podejście może być z powodzeniem użyte w aplikacjach wykorzystujących wirtualną rzeczywistość, w szczególności w grach edukacyjnych, których celem jest uatrakcyjnienie procesu zdobywania wiedzy. (Ocena działania Języka Opisu Gestów w roli bezdotykowego interfejsu w środowisku wirtualnej rzeczywistości).

Multi-Factor Authentication: A Survey

“…This approach could be easily combined with any text-input authentication methods as a typing pattern is unique for each person [119][120][121]. In case the MFA system is specifically developed for predefined gesture analysis [122], the user is required to replicate a previously learned movement while holding or wearing the sensing device [123][124][125].…”

Developing new robust motion templates of martial art techniques using R-GDL approach: a case study of SSCM

“…R-GDL method has been selected because of its capability to classify data from unsegmented (continues) recording for teachers' motions which contains multiple actions in order to generate the scripts . Furthermore, the teacher's motions involve large parts of body movement (Hachaj et al, 2017). R-GDL can generate syntactic descriptions which are easily understood by a computer programmer or an expert in the field.…”

“…Therefore, Gesture Description Language (GDL) and Reverse-Gesture Description Language (R-GDL) which are natural interface-based have been utilised in this paper to create the motion templates. GDL is a classifier capable for real-time human body gestures recognition Hachaj, 2016;Hachaj andOgiela, 2016a, 2016b) while R-GDL is an automatic scripts generator for gesture descriptions using unsupervised learning method (Hachaj et al, 2017;. Both approaches are created by Dr. Tomasz Hachaj and Professor Marek R. Ogiela from Pedagogical University of Krakow, Poland.…”

“…Both approaches do not require large training dataset . The most important is both approaches are natural user interfaces-based which are suitable for non-technical users to use them (Hachaj et al, 2017).…”