Similar to other descriptors, if the input image is colored, covert it silently to gray-level rather than terminating the execution

aruco: fix dictionaries format description

Face alignment (#1199)

* This commit will add a new functionality of one millisecond face_alignment to OpenCV.
Face alignment is a computer vision technology for identifying the geometric structure of human faces in digital images.
Given the location and size of a face, it automatically determines the shape
 of the face components such as eyes and nose.
Added following functions :
 1) Application to train a face landmark detector.
 2) Application to detect face landmarks using a trained model.
 3) Application to swap faces using face landmark detection
 4) Application to detect landmarks in a video.
Merged the code with a global facemark API.
Added Doxygen Documentation for the Class created.
Added tutorials for the samples added.
Added visualisations depicting error rate and training time.

Made desired changes

fix

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fix

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* face: drop duplicated file

-face_alignmentImpl.hpp
+face_alignmentimpl.hpp

* face: minor refactoring

- replace license headers
- fix usage of "precomp.hpp"

samples added

fix edgeboxes_demo

fix edgeboxes_demo

added edgeboxes bib

fix edgeboxes_demo

small fixes

fix edgeboxes_demo

fix warnings

fix warnings

small fixes

detectEdges needs rgb image instead bgr image.

Removed unnecessary protection

small fixes

- change face detector interface
- avoid using of legacy C-API defines
- simplify CV_Error()
- avoid using of legacy license headers

GSOC17 - Facemark API (#1257)

* Initial commit of facemark API

Initial structure of the facemark API and AAM header

* make training function as virtual

* Add: dataset parser

* Bug fix: clear the container before add points

* Add: AAM training - procrustes analysis

* Add AAM model

* Added training function for AAM

* Building bot fixes: remove training overload, explicit cast to float for atof

* + add dependency: imgcodecs

* Build bot fixes: add imgproc.hpp and type casting

* Building bot fix: type casting

* fixing the AAM training to match with Matlab version

fewer model parameters, change the image warp method, change the feature extraction method

* add: AAM fitting

added several functionalities for fitting

* fix warings

* Add: transformation for the initial fitting

* add sample file for aam implementation

* fix warning

* Add LFB Header

* loadTrainingData: Throw an error message if file not exist

* add: LBF prepare training data

* add: data augmentation

* change to double

* add: getMeanShape

* shuffling the dataset and parameters initialization

* add: initial structure of LBF class

* add: getDeltaShapes

Difference between the current shape and the desired shape

* add: random forest training

* generate lbf features

* global regression

* save training data

* fix the parameter initialization

* set the default parameters

* add: initial version of lbf sample

* update the current shape

* compute error

* add: prediction function

* fix some warnings

* fitting function

the result is mis-aligned, shuould be double checked

* add: fitting in the demo

* add dependencies

* Add: tutorial

* add: load model

* fixing training

* use user defined face detector

* Documents, tests, and samples

* Allow custom parameters

* Cleaning up

* Custom parameters for default detector, training, and get custom data

* AAM scales

* minor fixes , update the opencv_extra files

* change path to lbp cascade

* face: avoid memory leaks

* utilize the filestorage for the model, fixing some minor issues

* remove the liblinear dependency

* fix the aam test, avoiding to write any files

* use RNG and changes the test files