v0.4.0: adaptive regressor and HOG update, pre-trained model

[patrikhuber]

This is a major update to v0.4.0, containing additions and updates to the library and landmark detection.

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