open source pkg v1

pkg/OpenFace/matlab_version/face_validation/readme.txt

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+Code for facial landmark detection validation (knowing if detection succeeded), to be use for face tracking in videos so as not to do face detection every frame.
+
+To create the training data run:
+Create_data_train.m and Create_data_test.m
+
+The data generation code requires you to have the patch expert training data (Menpo, Multi-PIE and 300W data, not included) for positive examples, and inriaperson dataset for negative samples (not included as well). 
+
+To train Convolutional Neural Network based face landmark validation model use:
+Train_face_checker_cnn.m
+
+This will produce trained/face_checker_cnn_*.mat and trained/face_checker_cnn_*.txt files that can be used in C++ and matlab versions of OpenFace for face validation. Old versions can also be found in trained folder (they are simpler CNN models trained on smaller datasets).
+
+This will also produces tris*.txt files that can be used in the C++ version of the OpenFace,just place it in the lib\local\LandmarkDetector\model\detection_validation folder and edit the appropriate "main_*.txt" files. 
+
+The code uses piece-wise affine warping to a neutral shape with an CNN regressor for error estimation (see http://www.cl.cam.ac.uk/~tb346/ThesisFinal.pdf Section 4.6.2 for a very similar model but with SVR regressor)
+
+Dependencies:
+- vlfeat-0.9.20 and extract it in the current directory (http://www.vlfeat.org/download.html)
+- MatConvNet from http://www.vlfeat.org/matconvnet/ (tested with version 1.0-beta24), and install following the instructions
+
+Change the setup.m to match the locations of vlfeat and MatConvNet