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An Incremental Learning Based Gesture Recognition System for Consumer Devices Using Edge-Fog Computing
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DOI：10.1109/TCE.2019.2961066.png)
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摘要
En 中文
Gesture based systems are attracting more and more researchers to develop a single point control for consumer devices. Most of the existing works use wearable devices or camera based solutions, thus requiring additional resources. This paper presents an incremental learning based gesture recognition system that uses gyroscope sensor of Edge device (mobile phone) to recognize gesture of user and select the function of consumer device. Accelerometer sensor of the mobile phone is then used to control the magnitude of the selected function. User also gives speech input along with the gesture, which is recognized by the Fog device (laptop) and its result is used by the system for incremental learning. The system is implemented by developing an application on the mobile phone and various experiments are performed for validating the accuracy of the system.
Keyword:
Consumer devices
fog computing
gesture recognition
incremental learning
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