scholarly journals A Hand Gesture Recognition Method Based on Multi-Feature Fusion and Template Matching

2012 ◽  
Vol 29 ◽  
pp. 1678-1684 ◽  
Author(s):  
Liu Yun ◽  
Zhang Lifeng ◽  
Zhang Shujun
2020 ◽  
Vol 29 (6) ◽  
pp. 1153-1164
Author(s):  
Qianyi Xu ◽  
Guihe Qin ◽  
Minghui Sun ◽  
Jie Yan ◽  
Huiming Jiang ◽  
...  

2012 ◽  
Vol 33 (4) ◽  
pp. 476-484 ◽  
Author(s):  
Jun Cheng ◽  
Can Xie ◽  
Wei Bian ◽  
Dacheng Tao

2020 ◽  
pp. 1-1
Author(s):  
Guan Yuan ◽  
Xiao Liu ◽  
Qiuyan Yan ◽  
Shaojie Qiao ◽  
Zhixiao Wang ◽  
...  

Author(s):  
Julakanti Likhitha Reddy ◽  
Bhavya Mallela ◽  
Lakshmi Lavanya Bannaravuri ◽  
Kotha Mohan Krishna

To interact with world using expressions or body movements is comparatively effective than just speaking. Gesture recognition can be a better way to convey meaningful information. Communication through gestures has been widely used by humans to express their thoughts and feelings. Gestures can be performed with any body part like head, face, hands and arms but most predominantly hand is use to perform gestures, Hand Gesture Recognition have been widely accepted for numerous applications such as human computer interactions, robotics, sign language recognition, etc. This paper focuses on bare hand gesture recognition system by proposing a scheme using a database-driven hand gesture recognition based upon skin color model approach and thresholding approach along with an effective template matching with can be effectively used for human robotics applications and similar other applications .Initially, hand region is segmented by applying skin color model in YCbCr color space. Y represents the luminance and Cb and Cr represents chrominance. In the next stage Otsu thresholding is applied to separate foreground and background. Finally, template based matching technique is developed using Principal Component Analysis (PCA), k-nearest neighbour (KNN) and Support Vector Machine (SVM) for recognition. KNN is used for statistical estimation and pattern recognition. SVM can be used for classification or regression problems.


2013 ◽  
Vol 16 (12) ◽  
pp. 1393-1402 ◽  
Author(s):  
Guochao Chang ◽  
Jaewan Park ◽  
Chimin Oh ◽  
Chilwoo Lee

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