Model and implementation of body movement recognition using Support Vector Machines and Finite State Machines with cartesian coordinates input for gesture-based interaction

 

Autores
Bettio, Raphael W. de; Silva, André H. C.; Heimfarth, Tales; Freire, André P.; Sá, Alex G. C. de
Tipo de recurso
artículo
Estado
Versión publicada
Año de publicación
2013
País
Argentina
Institución
Universidad Nacional de La Plata
Repositorio
SEDICI (UNLP)
Descripción
The growth in the use of gesture-based interaction in video games has highlighted the potential for the use of such interaction method for a wide range of applications. This paper presents the implementation of an enhanced model for gesture recognition as input method for software applications. The model uses Support Vector Machines (SVM) and Finite State Machines (FSM) and the implementation was based on a Kinect R device. The model uses data input based on Cartesian coordinates. The use of Cartesian coordinates enables more flexibility to generalise the use of the model to different applications, when compared to related work encountered in the literature based on accelerometer devices for data input. The results showed that the use of SVM and FSM with Cartesian coordinates as input for gesture-based interaction is very promising. The success rate in gesture recognition was 98%, from a training corpus of 9 sets obtained by recording real users’ gestures. A proof-of-concept implementation of the gesture recognition interaction was performed using the application Google Earth(R). A preliminary acceptance evaluation with users indicated that the interaction with the system via the implementation reported was satisfactory.
Idioma
inglés
OAI Identifier
oai:sedici.unlp.edu.ar:10915/29803
Enlace del recurso
http://sedici.unlp.edu.ar/handle/10915/29803
http://hdl.handle.net/10915/29803
http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Oct13-3.pdf
Nivel de acceso
Acceso abierto
Materia
Ciencias Informáticas
Video (e.g., tape, disk, DVI)
COMPUTER GRAPHICS