Stereo Pose Machines - Real Time 3D Pose Estimation
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README.md

Stereo Pose Machines

demo

What it does:

  1. Compute 2D joints detected by CPM from stereo cameras
  2. Match the joints by guided patch-matching
  3. Triangulate the joints
  4. Build a 3D skeleton

Check out our Video Demo ! The project is a course demo and is not maintained.

Dependencies:

  • A pair of Pylon Cameras
  • Eigen3
  • OpenCV
  • tensorpack
  • PyYaml
  • PyOpenGL

Compile:

make -C src/cpp

Test Cameras:

cd src/cpp && ./main.bin

Two cameras could be detected in any order. To make the order consistent across runs, src/cpp/pylon_camera.cc assumes that the camera whose name contains "711" is the first camera. You'll need to change it for your case.

Calibrate Cameras:

Use main.bin to take images and use Kalibr to produce a yaml similar to the files in calibr-1211. Change the path in main.py to your own calibration results. Also change the undistortion coefficients in cpp/camera.hh.

Test CPM is working:

Download model to data/cpm.npy. See tensorpack CPM examples for instructions.

cd src/cpp && python2 main.py -t 'cpm-viewer'

It will use 2 GPU to run 2 CPMs in parallel.

Test 3D Visualization is working:

cd visualization && python2 main.py ../data/final-demo.npy

Its OpenGL bindings don't work on certain systems (e.g. Ubuntu). Don't know why.

Run Stereo CPM:

cd src/cpp && python2 main.py -t 'cpm3d'

This will send 3d point coordinates to 0.0.0.0:8888. You can use --host <ip address> to change the IP.

To start a server (maybe on some other computers) to receive points and visualize:

cd visualization && python main-server.py