/posenet-estimation

Primary LanguagePython

Fall - detection project - Video Classification analysis

Links to understand further:

Link-1 Link-2

Pre-requisites:

Understanding CNN, RNN, LSTM architecture

Creating Video Dataset

  • Create 5 videos under non-falling section (say Warm-up, Jump, Burpees, Walking, Push-ups, Sitting) and One falling video each of 60 seconds

  • Use the same camera for all video creation and convert them into 640 X 480 Pxl for our project

    • Camera used - iPhone SE 12 MP which gives 1920 X 1080

    • Click the image below to view for falling video

    • For Data set to do this project - Click here

    Sample video

Installing necessary Libraries

  1. create conda environment for our project

    conda create -n falldetection pip scipy pyyaml python=3.6

  2. Activate conda environment

    conda activate falldetection

  3. Install opencv-python and tensorflow 1.14 version

    pip install tensorflow==1.14
pip install opencv-python

  4. Clone Posenet link from github to local. Run webcam.py file. It must open the webcam and check whether it's identifying the skeletal points

  5. --To be Updated--

References

  1. Understanding CNN architecture
  2. --To be Updated--