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@patrikhuber patrikhuber released this 28 Jun 21:04
· 27 commits to master since this release
v0.4.0
3a63c15

This is a major update, containing additions and updates to the library and landmark detection.

The library now contains an implementation of the Robust Cascaded Regression facial landmark detection and features a pre-trained model. Using it requires only a couple of lines of code (see apps/rcr/rcr-detect.cpp).

Major changes to the library:

  • Added adaptive regressor update (NormalisationStrategy - e.g. inter-eye-distance dependent)
  • Changed from boost::serialization to cereal, and directly included the cereal headers into our project
  • Split the demo apps to: examples/, which contains hello-world examples for the library, and apps/, which contains more-involved apps like rcr-detect
  • Added the RCR code to the library under include/rcr/

Major changes to the RCR landmark detection:

  • Added adaptive HOG update, i.e. a different window-size and HOG parameters in each regressor level
  • Added a pre-trained landmark detection model with 22 landmarks

Minor changes:

  • rcr-train is build with openmp flags enabled
  • Set the CMake default to not build the tests and documentation
  • Updated the hello-world landmark detection to only train with 5 landmark
  • Changed code style to snake_case for variables and functions
  • "Included" vlhog (hog.c) in a header-only way
  • Enabled Visual Studio folders in CMake
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