A New Approach For Hand Gestures Recognition Based on Depth Map Captured by RGB-D Camera
Document title: A New Approach For Hand Gestures Recognition Based on Depth Map Captured by RGB-D Camera
Journal: Computación y sistemas
Database: PERIÓDICA
System number: 000410222
ISSN: 1405-5546
Authors: 1
1
2
1
Institutions: 1Multimedia, Information systems and Advanced Computing Laboratory, Sfax. Túnez
2Signal and System Research Unit, Tunis, Belvedere. Túnez
Year:
Season: Oct-Dic
Volumen: 20
Number: 4
Pages: 709-721
Country: México
Language: Inglés
Document type: Artículo
Approach: Experimental, aplicado
English abstract This paper introduces a new approach for hand gesture recognition based on depth Map captured by an RGB-D Kinect camera. Although this camera provides two types of information "Depth Map" and "RGB Image", only the depth data information is used to analyze and recognize the hand gestures. Given the complexity of this task, a new method based on edge detection is proposed to eliminate the noise and segment the hand. Moreover, new descriptors are introduce to model the hand gesture. These features are invariant to scale, rotation and translation. Our approach is applied on French sign language alphabet to show its effectiveness and evaluate the robustness of the proposed descriptors. The experimental results clearly show that the proposed system is very satisfactory as it to recognizes the French alphabet sign with an accuracy of more than 93%. Our approach is also applied to a public dataset in order to be compared in the existing studies. The results prove that our system can outperform previous methods using the same dataset
Disciplines: Ciencias de la computación
Keyword: Procesamiento de datos,
Lenguaje de señas,
Cámara Kinect,
Sensor de profundidad,
Reconocimiento de gestos
Keyword: Computer science,
Data processing,
Sign language,
Kinect camera,
Depth sensor,
Gesture recognition
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