Effective Gesture Based Framework for Capturing User Input
This work addresses input accessibility and cost reduction for users of mobile and computing devices, but it appears incremental as it builds on existing sensor and AI technologies for gesture recognition.
The researchers tackled the problem of traditional keyboard and mouse input by developing a gesture-based framework using image processing to create a virtual keyboard and mouse, achieving precise hand gesture detection with benefits like reduced peripheral costs and improved accessibility.
Computers today aren't just confined to laptops and desktops. Mobile gadgets like mobile phones and laptops also make use of it. However, one input device that hasn't changed in the last 50 years is the QWERTY keyboard. Users of virtual keyboards can type on any surface as if it were a keyboard thanks to sensor technology and artificial intelligence. In this research, we use the idea of image processing to create an application for seeing a computer keyboard using a novel framework which can detect hand gestures with precise accuracy while also being sustainable and financially viable. A camera is used to capture keyboard images and finger movements which subsequently acts as a virtual keyboard. In addition, a visible virtual mouse that accepts finger coordinates as input is also described in this study. This system has a direct benefit of reducing peripheral cost, reducing electronics waste generated due to external devices and providing accessibility to people who cannot use the traditional keyboard and mouse.