theAdityaNVS / Human-Activity-Recognisition

Human Activity Recognition using Machine Learning - Project

Aims to Recognise various Human Activities through Machine Learning Algorithms and input is given as video file

About

1. LSTM model from data set given under https://github.com/stuarteiffert/RNN-for-Human-Activity-Recognition-using-2D-Pose-Input

2. Using Detectron2 for pose estimation and the dataset is mapped to Detectron2 output format for training our LSTM model.

3. Currently the Model classifies the action into 6 categories

• "JUMPING",
• "HIGH JUMP",
• "PUNCHING",
• "HANDS UP",
• "WAVING HAND",
• "HANDS TOGETHER"

4. Using NgRok for webpage output and interaction page.

References

• Reference and credits from learnOpen CV.
• Original dataset is created using OpenPose