hand-gesture-recognition-using-mediapipe
MediaPipe(Python版)を用いて手の姿勢推定を行い、検出したキーポイントを用いて、簡易なMLPでハンドサインとフィンガージェスチャーを認識するサンプルプログラムです。（Estimate hand pose using MediaPipe(Python version). This is a sample program that recognizes hand signs and finger gestures with a simple MLP using the detected key points.）
mocapnet
We present MocapNET, a real-time method that estimates the 3D human pose directly in the popular Bio Vision Hierarchy (BVH) format, given estimations of the 2D body joints originating from monocular color images. Our contributions include: (a) A novel and compact 2D pose NSRM representation. (b) A human body orientation classifier and an ensemble of orientation-tuned neural networks that regress the 3D human pose by also allowing for the decomposition of the body to an upper and lower kinematic hierarchy. This permits the recovery of the human pose even in the case of significant occlusions. (c) An efficient Inverse Kinematics solver that refines the neural-network-based solution providing 3D human pose estimations that are consistent with the limb sizes of a target person (if known). All the above yield a 33% accuracy improvement on the Human 3.6 Million (H3.6M) dataset compared to the baseline method (MocapNET) while maintaining real-time performance
https://github.com/ai-forever/rsl_aij2023
AI Journey 2023: Russian Sign Language Recognition (Equal AI Track)
spark
Go handsfree with Spark and use hand gestures to increase your freedom and control the call
https://github.com/ai-forever/easy_sign
Easy_sign is an open source russian sign language recognition project that uses small CPU model for predictions and is designed for easy deployment via Streamlit.
hand-gesture-recognition_mediapipe
The aim of this Project is to detect and recognise the most common Hand Gestures expressed in Online Learning using Python and MediaPipe.
https://github.com/capjamesg/hand-pose-detection
Experiments with hand pose detection in Tensorflow.js.