Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Version 3.0 #39

Merged
merged 47 commits into from
Oct 14, 2019
Merged

Version 3.0 #39

merged 47 commits into from
Oct 14, 2019

Conversation

Tobias-Fischer
Copy link
Owner

@Tobias-Fischer Tobias-Fischer commented Oct 7, 2019

This pull request contains several major changes:

  • Use 3DDFA landmark extractor (https://github.com/cleardusk/3DDFA) as opposed to https://github.com/1adrianb/face-alignment because of the increased speed (note that we change the code so that Python 2 is still supported for use in ROS)
  • Refactor the code to disentangle ROS-independent code from ROS-specific code
  • Provide a standalone (non-ROS) version of the code
  • Provide helper script to download all required model files (this was done using ROS catkin scripts before)
  • Improve inference speed by doing inference in batches rather than per subject for landmark extraction as well as gaze estimation.
  • Run ensembles in parallel, so that running the 4-model ensemble is now very fast, too.
  • Tensorflow 2.0 compatibility

TODO before merging:

  • Update README to include the new libraries; make sure their LICENSE is included
  • Make sure 3DDFA works as well as the previous landmark extraction method
  • Run this branch on one of our wheelchairs to make sure that the changes are not breaking with the demos/research that is ongoing.
  • Decide whether the eye-blink work should be merged alongside this branch, or release a version with eye-blink support later (@twarz / Incorporate blink estimation #35) <- This will be merged separately.

TODO after merging:

Massive thanks to @ngageorange for a lot of input.

ahmed-alhindawi and others added 30 commits September 24, 2019 12:13
- batch landmark extraction onto GPU
- batch eye gaze estimation for multiple subjects
- modified ensembles to run on GPU in parallel using Keras (now run almost as quickly as single model file)
- various small bug fixes
…ector within RT-GENE

Made the face-encoding face tracker the default if no "use_face_encoding_tracker" variable is declared
@Tobias-Fischer
Copy link
Owner Author

Tobias-Fischer commented Oct 10, 2019

Breaking changes:

  • rename rgb_frame_id to ros_tf_frame in launch file, publisher is now in start_webcam.launch
  • interpupillary_distance is now set via dynamic_reconfigure rather than in the launch file
  • SequentialTracker is deprecated; to achieve a similar behavior use FaceEncodingTracker with a large face_encoding_threshold (see launch file)

Tobias-Fischer and others added 5 commits October 10, 2019 15:02
made the visualisation of the pose frames optional; setting visualise_headpose/visualise_eyepose to False gains ~10% performance improvement
@Tobias-Fischer Tobias-Fischer merged commit 43f6c47 into master Oct 14, 2019
@Tobias-Fischer Tobias-Fischer deleted the modularised branch October 14, 2019 09:03
@sahilrider
Copy link

sahilrider commented Oct 15, 2019

Hey, What's the eye-blink work?

@Tobias-Fischer
Copy link
Owner Author

Hi @sahilrider,
We will integrate a blink detection algorithm that we will present at the ICCV2019 gaze workshop (https://gazeworkshop.github.io/#accepted). Please check back in the following weeks for more details.

Best, Tobias

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

Successfully merging this pull request may close these issues.

Provide standalone (non-ROS) script Improve computational speed for multi person estimation
3 participants