The Design and Implementation of a Gesture-Driven System for Intelligent Wheelchairs Based on the Orientation Histogram Method

2011 ◽  
Vol 320 ◽  
pp. 616-619
Author(s):  
Yuan Luo ◽  
Yu Xie
Keyword(s):  
Gesture Recognition ◽  
Hand Gesture Recognition ◽  
Characteristic Vector ◽  
Experimental Results ◽  
Hand Gesture ◽  
Histogram Method ◽  
Design And Implementation ◽  
Orientation Histogram ◽  
Driven System

An approach of hand gesture recognition, setting the orientation histogram of the picture as the characteristic vector of hand gesture, is discussed in this paper. It can decrease the influence of light changes during the process of recognition effectively. A gesture-Driven system for intelligent wheelchairs is also introduced in the paper. Experimental results show that the method is robust and accurate.

Invariant Hand Gesture Recognition System

2018 ◽  
Vol 7 (4.6) ◽  
pp. 299
Author(s):  
G. N. Balaji ◽  
S. V. Suryanarayana ◽  
C. Veeramani
Keyword(s):  
Gesture Recognition ◽  
Recognition System ◽  
Vital Role ◽  
Hand Gesture Recognition ◽  
Support Vector ◽  
Hand Gesture ◽  
3D Analysis ◽  
Orientation Histogram ◽  
Hand Gestures Recognition ◽  
Hand Image

Hand gesture recognition plays a vital role in numerous applications, which can run from mobile phones to 3D analysis of anatomy and from gaming to medicinal science. In a large portion of research applications and current business hand gestures recognition, has been implemented by utilizing either vision based or sensor-based gloves strategies where hues, paperclips of synthetic substances are used on to capture the gestures. Another essential issue associated with vision-based procedures is illuminated conditions. The threshold used for the segmentation is changed based on the light variations. A system is proposed in this paper, which extracts the gesture part from the hand image by preprocessing, followed by extraction of orientation histogram based feature is done. Further, in order to recognize the gestures, the extracted HOG feature vectors are provide for support vector machine (SVM). The proposed system is tested with 84 images and it outperforms with an accuracy of 94.04%.  

scholarly journals Invariant Hand Gesture Recognition System

2018 ◽  
Vol 7 (4.6) ◽  
pp. 299
Author(s):  
G. N. Balaji ◽  
S. V. Suryanarayana ◽  
C. Veeramani
Keyword(s):  
Gesture Recognition ◽  
Recognition System ◽  
Vital Role ◽  
Hand Gesture Recognition ◽  
Support Vector ◽  
Hand Gesture ◽  
3D Analysis ◽  
Orientation Histogram ◽  
Hand Gestures Recognition ◽  
Hand Image

Hand gesture recognition plays a vital role in numerous applications, which can run from mobile phones to 3D analysis of anatomy and from gaming to medicinal science. In a large portion of research applications and current business hand gestures recognition, has been implemented by utilizing either vision based or sensor-based gloves strategies where hues, paperclips of synthetic substances are used on to capture the gestures. Another essential issue associated with vision-based procedures is illuminated conditions. The threshold used for the segmentation is changed based on the light variations. A system is proposed in this paper, which extracts the gesture part from the hand image by preprocessing, followed by extraction of orientation histogram based feature is done. Further, in order to recognize the gestures, the extracted HOG feature vectors are provide for support vector machine (SVM). The proposed system is tested with 84 images and it outperforms with an accuracy of 94.04%.  

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