Deep Fisher discriminant learning for mobile hand gesture recognition
نویسندگان
چکیده
منابع مشابه
Deep Fisher discriminant learning for mobile hand gesture recognition
Gesture recognition is a challenging problem in the field of biometrics. In this paper, we integrate Fisher criterion into Bidirectional Long-Short Term Memory (BLSTM) network and Bidirectional Gated Recurrent Unit (BGRU), thus leading to two new deep models termed as F-BLSTM and F-BGRU. Both Fisher discriminative deep models can effectively classify the gesture based on analyzing the accelerat...
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With the rapid emergence of 3D applications and virtual environments in computer systems; the need for a new type of interaction device arises. This is because the traditional devices such as mouse, keyboard, and joystick become inefficient and cumbersome within these virtual environments. In other words, evolution of user interfaces shapes the change in the Human-Computer Interaction (HCI). In...
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With the rapid emergence of 3D applications and virtual environments in computer systems; the need for a new type of interaction device arises. This is because the traditional devices such as mouse, keyboard, and joystick become inefficient and cumbersome within these virtual environments. In other words, evolution of user interfaces shapes the change in the Human-Computer Interaction (HCI). In...
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Hand gesture recognition has been a major challenge during the recent years. Many of the hand gesture recognition systems however, have been restricted to a few number of possible movements. Some applications such as gesture recognition in understanding sign languages, include a large number of classes and need an automatic learning method for extracting the features of each class. An important...
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ژورنال
عنوان ژورنال: Pattern Recognition
سال: 2018
ISSN: 0031-3203
DOI: 10.1016/j.patcog.2017.12.023