Skip to content

Latest commit

 

History

History
13 lines (10 loc) · 738 Bytes

Readme.md

File metadata and controls

13 lines (10 loc) · 738 Bytes

About

Machine learning using RNN LSTM with Keras on UTD-MHAD Kinect dataset (Depth, Inertial, Skeleton). This is an assignment from NUS ISS SenseMaking course.

Activity Classification

Please refer to jupyter notebook file "activity_classification.ipynb", here we choose only inertial dataset and 3 actvities (hand swipe, two hands push, jogging) for sequence classification.

Visualization

Run command python depth_data_visualizer.py in terminal launch visualizer tool. User can select action, subject and trial to show the 240 x 320 depth videos