Hand Gesture Recognition Software Based on Indian Sign Language

被引:0
|
作者
Kadam, Sanket [1 ]
Ghodke, Aakash [1 ]
Sadhukhan, Sumitra [1 ]
机构
[1] Rajiv Gandhi Inst Technol, AICTE Affiliated, Dept Comp Engn, Mumbai, Maharashtra, India
关键词
contour detection; epipolar detection; camera calibration; ISL; 3D modelling; Deep neural network; convolution neural network;
D O I
10.1109/iciict1.2019.8741512
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Hand gestures are a powerful environment for communicating with communities with intellectual disability. It is useful for connecting people and computers. The expansion potential of this system can be known in public places where deaf people are communicating with ordinary people to send messages. In this article, we have provided a system of recognizing gestures continuously with the Indian Sign Language (ISL), which both hands are used to make every gesture. Gesture recognition continues to be a daunting task. We tried to fix this problem using the key download method. These key tips are useful for breaking down the sign language gestures into the order of the characters, as well as deleting unsupported frameworks. After the splitting gear breaks each character is regarded as a single and unique gesture. Pre-processing gestures are obtained using histogram (OH) with PCA to reduce the dimensions of the traits obtained after OH. The experiments were performed on our live ISL dataset, which was created using an existing camera.
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页数:5
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