Tiny ML for gesture recognition
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Date
2023
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Publisher
Université d'Oum El Bouaghi
Abstract
This project aims to develop a gesture recognition application for 06 classes and more using TinyML technics and a tiny board for a wearable application. Gesture recognition has become a captivating field of study and application, driven by advancements in technologies like edge impulse platform , devices such as Arduino and the XIAO BLE SENSE board. By integrating sensors like IMU (Inertial Measurement Unit) with microcontrollers (MCUs), complex motions can be captured and analyzed. The combination of machine learning and microcontrollers, known as TinyML, has enabled the deployment of neural networks (NNs) directly on these small devices. Popular frameworks like TensorFlow, TensorFlow Lite, and Keras empower developers to train and deploy efficient models for gesture recognition, revolutionizing the way we interact with machines. With the power of these tools, accurate and real-time recognition of gestures can now be achieved, opening up exciting possibilities in various domains such as gaming, robotics, and human-computer interaction
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Keywords
Gesture recognition; Edge impulse platform; Arduino; XIAO ble sense board; TinyML;TensorFlow, , , , , ,