skeh/head-pose-estimation
1
0
Fork 0
Code Issues Pull requests Projects Releases Wiki Activity
No description
90 commits 4 branches 0 tags 139 MiB
PureBasic 99.9%
Find a file
yinguobing 0239cd9b85 typo fix
2018-01-29 13:43:14 +08:00
assets add 3D model of 68 points 2018-01-25 19:02:15 +08:00
.gitignore Initial commit 2017-12-27 15:23:36 +08:00
demo.gif update demo gif 2018-01-26 08:47:32 +08:00
demo1.gif add more demo gif 2018-01-26 08:57:01 +08:00
estimate_head_pose.py typo fix 2018-01-29 13:43:14 +08:00
LICENSE Initial commit 2017-12-27 15:23:36 +08:00
mark_detector.py MarkDetector is a class now 2018-01-17 09:46:15 +08:00
optical_flow_tracker.py use optical flow tracker to update kalman filter parameters 2017-12-29 10:26:37 +08:00
pose_estimator.py update annotation drawing function to accept custom line width 2018-01-25 14:22:07 +08:00
README.md Update README.md 2018-01-29 10:35:49 +08:00
stabilizer.py bug fix: initialize parameters according to state_num 2018-01-12 13:37:17 +08:00

README.md

Head pose estimation

This repo shows how to estimate human head pose from videos using TensorFlow and OpenCV.

demo demo

How it works

There are three major steps:

  1. Face detection. A face detector is adopted to provide a face box containing a human face. Then the face box is expanded and transformed to a square to suit the needs of later steps.

  2. Facial landmark detection. A custom trained facial landmark detector based on TensorFlow is responsible for output 68 facial landmarks.

  3. Pose estimation. Once we got the 68 facial landmarks, a mutual PnP algorithms is adopted to calculate the pose.

Miscellaneous

  • The marks is detected frame by frame, which result in small variance between adjacent frames. This makes the pose unstaible. A Kalman filter is used to solve this problem, you can draw the original pose to observe the difference.

  • The 3D model of face comes from OpenFace, you can find the original file here.

License

The code is licensed under the MIT license. However, the pre-trained TensorFlow model file is trained with various public data sets which have their own licenses. Please refer to them before using this code.