Facial landmark detection, Another Great results from Czech Republic

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  • Facial landmark detector

    Flandmark detection

    This is another great result of Czech school of computer vision. Facial landmark detector was developed at Czech Technical University in Prague, Center for Machine Perception mainly by Michal Uřičák and Vojtěch Franc. 
    They are both work for Eydea on commertial products if I remember correctly.

    This is me on the video using opencv 3 under Visual Studio 2015 with Clandmark Lib. I have no use in mine products but its pretty cool playing with this in free time. This is great cross platform lib for Iphone Android Applications and also for Windows 10 Universal Apps.

    Look at a video at the original project page. I experimented a bit with floating point precision in a solver. And the results are a little bit worse. :)


    Here is links to Original web page of the projects with broader description.

    Fmandmark

    Flandmark is an open source C library (with interface to MATLAB) implementing a facial landmark detector in static images.

    Clandmark

    CLandmark is an open-source facial landmark lib. Written in C++. The next great generation of Flandmark.
    References are taken from both projects site.

    [1] M. Uricar, V. Franc, D. Thomas, A. Sugimoto, and V. Hlavac, Real-time Multi-view Facial Landmark Detector Learned by the Structured Output SVM, BWILD '15: International Workshop on Biometrics in the Wild, 2015.

    [2] M. Uricar, V. Franc and V. Hlavac, Detector of Facial Landmarks Learned by the Structured Output SVM, VISAPP '12: Proceedings of the 7th International Conference on Computer Vision Theory and Applications, 2012. Received Best Paper Award 

    [3] M. Uricar, Detector of facial landmarks, Master's Thesis, supervised by V. Franc, May 2011. [pdf]
    J. Sivic, M. Everingham and A. Zisserman, "Who are you?" - Learning Person Specific Classifiers from Video, Proc. of IEEE Conference on Computer Vision and Pattern Recognition, 2009. 

    [4] G. B. Huang, M. Ramesh, T. Berg and E. Learned-Miller, Labeled faces in the wild: A database for studying face recognition in unconstrained environments, Technical Report 07-49. University of Massachusetts, Amherst, 2007. 

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