gesture-classification

Unified learning approach for egocentric hand gesture recognition and fingertip detection.

Detection and classification of head gestures in videos

A simple hand gesture recognition algorithm using tensorflow and mediapipe

Team project for 700.401 (24W) Pervasive Computing Lab at University of Klagenfurt

Hand gesture classification by optomyographical sensor signals

Computationally-free personalization at test time for sEMG gesture classification. Fast (gpu/cpu) ninapro API.

Skin segmentation is basic and key in the hand gesture recognition. Since skin color is within a threshold range, thresholding a color space, we can swiftly segment the desired region.

Classifies rock-paper-scissors hand gestures from optically pumped magnetometer (OPM) data recorded at the University of Nottingham.

EMG-based hand gesture classification on NinaPro DB5 using PyTorch MLP with SHAP and LIME explainability — identifying which forearm muscles drive each prediction for transparent prosthetic control.

Gesture classification in real time using a CNN, dedicated for Antmicro's TX2/TX2i Deep Learning Kit.

🖐 Real-time hand gesture classifier — detects wave, stop & thumbs_up using MediaPipe's 21-point hand skeleton + Random Forest. Supports live webcam inference and Kaggle dataset training.

A gesture-controlled camera app that takes a photo when you give a thumbs up to your webcam. Built with Python, OpenCV, and MediaPipe