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Smart Touchless Control Radar


This project is in fulfillment of NTU-EEE's EE3080 Design & Innovation Project.

  • Project Title: E047 Smart Touchless control with Millimeter-Wave Radar Sensor and Artificial Intelligence
  • Supervisor: Prof Lu Yilong
  • Laboratory: Media Technology Lab (Loc: S2.2-B4-02)
  • Group Members: Philip, Yi Wen (A), Wai Yeong (A), Davis (B), Jun De (B)

Useful Links


Folder Structure

  • Folders with the prefix acconeer are sample/setup references files forked from Acconeer's GitHub.
  • The main directory is final-pipeline, which contains all the finalised files used.
  • Project admin-related files like Project Charter and Project Report are password protected for the time being.
  • Please do not re-order the directories as the paths are resolved using the current directory tree.

Running the Gesture Recognition Script

  • Run final-pipeline/final-realtime-hybrid.py.

usage: final-realtime-hybrid.py [-h] [-rpi] [-kb]

DIP E047: Final Real-time Gesture Prediction

optional arguments:
  -h, --help   show this help message and exit
  -rpi, --rpi  Raspberry Pi mode to fix port
  -kb, --kb    Keyboard presses

Running the Menu Application

  • Run final-pipeline/restaurant-menu.py with the -kb flag on the previous script final-pipeline/final-realtime-hybrid.py.


GUI for Gesture Extraction

  • final-pipeline/gesture_extractor_gui.py is a Python script developed to automate the process of extracting gesture samples from a continous recording obtained from the GUI tool provided by Acconeer. This fixes the alignment issue faced when recording one sample at a time.

  • The tool saves extracted samples in .npz format with the intention of a small file size. To read data from these new files, please use np.load('filename-000.npz')['sample'], where filename is a placeholder.

  • For ease of running the tool, an alternative Windows executable file final-pipeline/gesture_extractor_gui.exe is available too.

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