This repository contains a calibration free gaze tracking system based on freely available libraries and data sets. The system is able to estimate horizontal and vertical gaze directions as well as eye closeness. A system description will be available in:

• Lars Schillingmann and Yukie Nagai, "Yet Another Gaze Detector: An Embodied Calibration Free System for the iCub Robot", 15th IEEE RAS Humanoids Conference on Humanoid Robots, 2015

Please cite the above paper when using this module for your research.

Make sure you have the following dependencies available / installed:

• QT5: http://www.qt.io/download/
• opencv 2.x.x: http://opencv.org/downloads.html
• boost: http://www.boost.org/
• dlib: http://dlib.net/
• run getFaceAlignmentModel.sh in the data directory to download dlib's face alignment model which is required for running gazetool.

Compiling

• gazetool uses cmake, thus a standard cmake configure run is required: mkdir build && cd build && cmake ..
• run make
• run make install

• Run gazetool.sh -c 0 to use the first webcam attached to your system

• Sync to vblank might negatively affect performance
  • A QT bug might further limit the maximum framerate when using multiple QT GLWidgets
• Some BLAS implementations automatically use multithreading which seems to negatively affect performance in our case.
  • If openblas is used as default blas implementation: set the environment variable OPENBLAS_NUM_THREADS=1
• Optimization notes
• Include architecture specific optimzation flags such as -march=native -O3 in CMAKE_CXX_FLAGS
• Enable USE_AVX_INSTRUCTIONS, USE_SSE2_INSTRUCTIONS, or USE_SSE4_INSTRUCTIONS if applicable (used by dlib)
• make sure blas and lapack libraries are installed
• gazetool should be able to process 640x480 input at 30fps on most recent machines (including notebooks)

• F. Timm and E. Barth, “Accurate eye centre localisation by means of gradients,” in Proceedings of the International Conference on Computer Vision Theory and Applications, 2011, vol. 1, pp. 125–130.

• F. Timm and E. Barth, “Accurate, fast, and robust centre localisation for images of semiconductor components,” 2011, vol. 7877, no. 0, pp. 787705–787705–10.

• https://github.com/trishume/eyeLike

• D. E. King, “Dlib-ml: A Machine Learning Toolkit,” J. Mach. Learn. Res., vol. 10, pp. 1755–1758, Dec. 2009.

• F. Song, X. Tan, X. Liu, and S. Chen, “Eyes closeness detection from still images with multi-scale histograms of principal oriented gradients,” Pattern Recognit., vol. 47, no. 9, pp. 2825–2838, Sep. 2014.

• B. A. Smith, Q. Yin, S. K. Feiner, and S. K. Nayar, “Gaze locking: passive eye contact detection for human-object interaction,” in Proceedings of the 26th annual ACM symposium on User interface software and technology - UIST ’13, 2013, pp. 271–280.