Encode and decode hand movements using C# and Kinect. Based on K-means and Hidden Markov Models.
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Updated
Aug 2, 2020 - C#
Encode and decode hand movements using C# and Kinect. Based on K-means and Hidden Markov Models.
🖐 An implementation of a machine learning model for detecting and recognizing hand signs (0-5) accurately using Python. The project pipeline involves the following modules: Preprocessing, Feature Extraction, Model selection and training, and finally performance analysis.
Mediapipe hand-signs UI for video snipping control
This project presents a deep learning-driven approach for hand gesture recognition in virtual museums using a combinaison of CNN and LSTM.
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Showcasing a state-of-the-art hand gesture recognition system based on Convolutional Neural Networks (CNNs), this repository features a fluid interface for human-computer interaction. It excels in classifying a wide array of gestures, catering to applications in virtual reality, gaming, assistive technology, and beyond.
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Computer Vision application to recognize hand-gestures by counting fingers
a vertical scroller game where players steer their spaceship with hand movements, dodging asteroids and aiming for high scores.
A simple AR app that tracks hand gestures and position.
Computer Vision project to test hand detection and gesture classification to control IoT devices over the network.
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