Computer Vision and Machine Learning based Hand Gesture Recognition - Tapa blanda

Ribeiro, Fernando; Reis, Luís Paulo; Trigueiros, Paulo

 
9783639763966: Computer Vision and Machine Learning based Hand Gesture Recognition
Tapa blanda
ISBN 10: 3639763963 ISBN 13: 9783639763966
Editorial: Scholars’ Press, 2015

Sinopsis

Hand gestures are a powerful way for human communication, with lots of potential applications in the area of human computer interaction. Vision-based hand gesture recognition techniques have many proven advantages compared with traditional devices. Hand gesture recognition is a difficult problem and the current work is only a small contribution towards achieving the results needed in the field. The main objective of this work was to study and implement solutions that could be generic enough, with the help of machine learning algorithms, allowing its application in a wide range of human-computer interfaces, for online gesture recognition. To achieve this, a set of implementations for processing and retrieving hand user information, learn statistical models and able to do online classification were created. The final prototype is a generic solution able to interpret static and dynamic gestures and that can be integrated with any human robot/system interface. The implemented solution, is easily configured to learn different static and dynamic gestures, while creating statistical models that can be used in any real-time user interface for online gesture classification.

"Sinopsis" puede pertenecer a otra edición de este libro.

Reseña del editor

Hand gestures are a powerful way for human communication, with lots of potential applications in the area of human computer interaction. Vision-based hand gesture recognition techniques have many proven advantages compared with traditional devices. Hand gesture recognition is a difficult problem and the current work is only a small contribution towards achieving the results needed in the field. The main objective of this work was to study and implement solutions that could be generic enough, with the help of machine learning algorithms, allowing its application in a wide range of human-computer interfaces, for online gesture recognition. To achieve this, a set of implementations for processing and retrieving hand user information, learn statistical models and able to do online classification were created. The final prototype is a generic solution able to interpret static and dynamic gestures and that can be integrated with any human robot/system interface. The implemented solution, is easily configured to learn different static and dynamic gestures, while creating statistical models that can be used in any real-time user interface for online gesture classification.

"Sobre este título" puede pertenecer a otra edición de este libro.

Editorial
Scholars’ Press
Año de publicación
2015
Idioma
Inglés
ISBN 10 
3639763963
ISBN 13 
9783639763966
Encuadernación
Tapa blanda
Número de páginas
220
Contacto del fabricante
no disponible
Persona responsable
no disponible