Doxygen documentation for all modules

modules/adas/include/opencv2/adas.hpp

@@ -38,3 +38,7 @@ or tort (including negligence or otherwise) arising in any way out of
 the use of this software, even if advised of the possibility of such damage.
 
 */
+
+/** @defgroup adas Advanced Driver Assistance
+*/
+

modules/bgsegm/doc/bgsegm.bib

+@incollection{KB2001,
+  title={An improved adaptive background mixture model for real-time tracking with shadow detection},
+  author={KaewTraKulPong, Pakorn and Bowden, Richard},
+  booktitle={Video-Based Surveillance Systems},
+  pages={135--144},
+  year={2002},
+  publisher={Springer}
+}
+
+@inproceedings{Gold2012,
+  title={Visual tracking of human visitors under variable-lighting conditions for a responsive audio art installation},
+  author={Godbehere, Andrew B and Matsukawa, Akihiro and Goldberg, Ken},
+  booktitle={American Control Conference (ACC), 2012},
+  pages={4305--4312},
+  year={2012},
+  organization={IEEE}
+}

modules/bgsegm/include/opencv2/bgsegm.hpp

@@ -44,21 +44,21 @@ the use of this software, even if advised of the possibility of such damage.
 
 #ifdef __cplusplus
 
+/** @defgroup bgsegm Improved Background-Foreground Segmentation Methods
+*/
+
 namespace cv
 {
 namespace bgsegm
 {
 
-/*!
- Gaussian Mixture-based Backbround/Foreground Segmentation Algorithm
+//! @addtogroup bgsegm
+//! @{
 
- The class implements the following algorithm:
- "An improved adaptive background mixture model for real-time tracking with shadow detection"
- P. KadewTraKuPong and R. Bowden,
- Proc. 2nd European Workshp on Advanced Video-Based Surveillance Systems, 2001."
- http://personal.ee.surrey.ac.uk/Personal/R.Bowden/publications/avbs01/avbs01.pdf
+/** @brief Gaussian Mixture-based Background/Foreground Segmentation Algorithm.
 
-*/
+The class implements the algorithm described in @cite KB2001.
+ */
 class CV_EXPORTS_W BackgroundSubtractorMOG : public BackgroundSubtractor
 {
 public:
@@ -75,54 +75,118 @@ public:
     CV_WRAP virtual void setNoiseSigma(double noiseSigma) = 0;
 };
 
+/** @brief Creates mixture-of-gaussian background subtractor
+
+@param history Length of the history.
+@param nmixtures Number of Gaussian mixtures.
+@param backgroundRatio Background ratio.
+@param noiseSigma Noise strength (standard deviation of the brightness or each color channel). 0
+means some automatic value.
+ */
 CV_EXPORTS_W Ptr<BackgroundSubtractorMOG>
     createBackgroundSubtractorMOG(int history=200, int nmixtures=5,
                                   double backgroundRatio=0.7, double noiseSigma=0);
                                   
-/**
- * Background Subtractor module. Takes a series of images and returns a sequence of mask (8UC1)
- * images of the same size, where 255 indicates Foreground and 0 represents Background.
- * This class implements an algorithm described in "Visual Tracking of Human Visitors under
- * Variable-Lighting Conditions for a Responsive Audio Art Installation," A. Godbehere,
- * A. Matsukawa, K. Goldberg, American Control Conference, Montreal, June 2012.
+
+/** @brief Background Subtractor module based on the algorithm given in @cite Gold2012.
+
+ Takes a series of images and returns a sequence of mask (8UC1)
+ images of the same size, where 255 indicates Foreground and 0 represents Background.
+ This class implements an algorithm described in "Visual Tracking of Human Visitors under
+ Variable-Lighting Conditions for a Responsive Audio Art Installation," A. Godbehere,
+ A. Matsukawa, K. Goldberg, American Control Conference, Montreal, June 2012.
  */
 class CV_EXPORTS_W BackgroundSubtractorGMG : public BackgroundSubtractor
 {
 public:
+    /** @brief Returns total number of distinct colors to maintain in histogram.
+    */
     CV_WRAP virtual int getMaxFeatures() const = 0;
+    /** @brief Sets total number of distinct colors to maintain in histogram.
+    */
     CV_WRAP virtual void setMaxFeatures(int maxFeatures) = 0;
 
+    /** @brief Returns the learning rate of the algorithm.
+
+    It lies between 0.0 and 1.0. It determines how quickly features are "forgotten" from
+    histograms.
+     */
     CV_WRAP virtual double getDefaultLearningRate() const = 0;
+    /** @brief Sets the learning rate of the algorithm.
+    */
     CV_WRAP virtual void setDefaultLearningRate(double lr) = 0;
 
+    /** @brief Returns the number of frames used to initialize background model.
+    */
     CV_WRAP virtual int getNumFrames() const = 0;
+    /** @brief Sets the number of frames used to initialize background model.
+    */
     CV_WRAP virtual void setNumFrames(int nframes) = 0;
 
+    /** @brief Returns the parameter used for quantization of color-space.
+
+    It is the number of discrete levels in each channel to be used in histograms.
+     */
     CV_WRAP virtual int getQuantizationLevels() const = 0;
+    /** @brief Sets the parameter used for quantization of color-space
+    */
     CV_WRAP virtual void setQuantizationLevels(int nlevels) = 0;
 
+    /** @brief Returns the prior probability that each individual pixel is a background pixel.
+    */
     CV_WRAP virtual double getBackgroundPrior() const = 0;
+    /** @brief Sets the prior probability that each individual pixel is a background pixel.
+    */
     CV_WRAP virtual void setBackgroundPrior(double bgprior) = 0;
 
+    /** @brief Returns the kernel radius used for morphological operations
+    */
     CV_WRAP virtual int getSmoothingRadius() const = 0;
+    /** @brief Sets the kernel radius used for morphological operations
+    */
     CV_WRAP virtual void setSmoothingRadius(int radius) = 0;
 
+    /** @brief Returns the value of decision threshold.
+
+    Decision value is the value above which pixel is determined to be FG.
+     */
     CV_WRAP virtual double getDecisionThreshold() const = 0;
+    /** @brief Sets the value of decision threshold.
+    */
     CV_WRAP virtual void setDecisionThreshold(double thresh) = 0;
 
+    /** @brief Returns the status of background model update
+    */
     CV_WRAP virtual bool getUpdateBackgroundModel() const = 0;
+    /** @brief Sets the status of background model update
+    */
     CV_WRAP virtual void setUpdateBackgroundModel(bool update) = 0;
 
+    /** @brief Returns the minimum value taken on by pixels in image sequence. Usually 0.
+    */
     CV_WRAP virtual double getMinVal() const = 0;
+    /** @brief Sets the minimum value taken on by pixels in image sequence.
+    */
     CV_WRAP virtual void setMinVal(double val) = 0;
 
+    /** @brief Returns the maximum value taken on by pixels in image sequence. e.g. 1.0 or 255.
+    */
     CV_WRAP virtual double getMaxVal() const = 0;
+    /** @brief Sets the maximum value taken on by pixels in image sequence.
+    */
     CV_WRAP virtual void setMaxVal(double val) = 0;
 };
 
+/** @brief Creates a GMG Background Subtractor
+
+@param initializationFrames number of frames used to initialize the background models.
+@param decisionThreshold Threshold value, above which it is marked foreground, else background.
+ */
 CV_EXPORTS_W Ptr<BackgroundSubtractorGMG> createBackgroundSubtractorGMG(int initializationFrames=120,
                                                                         double decisionThreshold=0.8);                                  
 
+//! @}
+
 }
 }
 

modules/bioinspired/doc/bioinspired.bib

+@article{Benoit2010,
+  title={Using human visual system modeling for bio-inspired low level image processing},
+  author={Benoit, Alexandre and Caplier, Alice and Durette, Barth{\'e}l{\'e}my and H{\'e}rault, Jeanny},
+  journal={Computer vision and Image understanding},
+  volume={114},
+  number={7},
+  pages={758--773},
+  year={2010},
+  publisher={Elsevier}
+}
+
+@inproceedings{Strat2013,
+  title={Retina enhanced SIFT descriptors for video indexing},
+  author={Strat, Sabin Tiberius and Benoit, Alexandre and Lambert, Patrick},
+  booktitle={Content-Based Multimedia Indexing (CBMI), 2013 11th International Workshop on},
+  pages={201--206},
+  year={2013},
+  organization={IEEE}
+}
+
+@book{Herault2010,
+  title={Vision: Images, Signals and Neural Networks-Models of Neural Processing in Visual Perception},
+  author={Jeanny, Herault},
+  year={2010},
+  publisher={World Scientific}
+}
+
+@inproceedings{Chaix2007,
+  title={Efficient demosaicing through recursive filtering},
+  author={De Lavar{\`e}ne, Brice Chaix and Alleysson, David and Durette, Barth{\'e}l{\'e}my and H{\'e}rault, Jeanny},
+  booktitle={Image Processing, 2007. ICIP 2007. IEEE International Conference on},
+  volume={2},
+  pages={II--189},
+  year={2007},
+  organization={IEEE}
+}
+
+@article{Meylan2007,
+  title={Model of retinal local adaptation for the tone mapping of color filter array images},
+  author={Meylan, Laurence and Alleysson, David and S{\"u}sstrunk, Sabine},
+  journal={JOSA A},
+  volume={24},
+  number={9},
+  pages={2807--2816},
+  year={2007},
+  publisher={Optical Society of America}
+}

modules/bioinspired/doc/bioinspired.rst

@@ -7,4 +7,4 @@ The module provides biological visual systems models (human visual system and ot
 .. toctree::
     :maxdepth: 2
 
-    Human retina documentation <retina/index>
+    Human retina documentation <retina>

modules/bioinspired/include/opencv2/bioinspired.hpp

@@ -47,4 +47,14 @@
 #include "opencv2/bioinspired/retina.hpp"
 #include "opencv2/bioinspired/retinafasttonemapping.hpp"
 #include "opencv2/bioinspired/transientareassegmentationmodule.hpp"
+
+/** @defgroup bioinspired Biologically inspired vision models and derivated tools
+
+The module provides biological visual systems models (human visual system and others). It also
+provides derivated objects that take advantage of those bio-inspired models.
+
+@ref bioinspired_retina
+
+*/
+
 #endif

modules/bioinspired/include/opencv2/bioinspired/retinafasttonemapping.hpp

@@ -67,11 +67,10 @@
 #ifndef __OPENCV_BIOINSPIRED_RETINAFASTTONEMAPPING_HPP__
 #define __OPENCV_BIOINSPIRED_RETINAFASTTONEMAPPING_HPP__
 
-/*
- * retinafasttonemapping.hpp
- *
- *  Created on: May 26, 2013
- *      Author: Alexandre Benoit
+/**
+@file
+@date May 26, 2013
+@author Alexandre Benoit
  */
 
 #include "opencv2/core.hpp" // for all OpenCV core functionalities access, including cv::Exception support
@@ -79,43 +78,61 @@
 namespace cv{
 namespace bioinspired{
 
-/**
- * a wrapper class which allows the tone mapping algorithm of Meylan&al(2007) to be used with OpenCV.
- * This algorithm is already implemented in thre Retina class (retina::applyFastToneMapping) but used it does not require all the retina model to be allocated. This allows a light memory use for low memory devices (smartphones, etc.
- * As a summary, these are the model properties:
- * => 2 stages of local luminance adaptation with a different local neighborhood for each.
- * => first stage models the retina photorecetors local luminance adaptation
- * => second stage models th ganglion cells local information adaptation
- * => compared to the initial publication, this class uses spatio-temporal low pass filters instead of spatial only filters.
- * ====> this can help noise robustness and temporal stability for video sequence use cases.
- * for more information, read to the following papers :
- *  Meylan L., Alleysson D., and Susstrunk S., A Model of Retinal Local Adaptation for the Tone Mapping of Color Filter Array Images, Journal of Optical Society of America, A, Vol. 24, N 9, September, 1st, 2007, pp. 2807-2816Benoit A., Caplier A., Durette B., Herault, J., "USING HUMAN VISUAL SYSTEM MODELING FOR BIO-INSPIRED LOW LEVEL IMAGE PROCESSING", Elsevier, Computer Vision and Image Understanding 114 (2010), pp. 758-773, DOI: http://dx.doi.org/10.1016/j.cviu.2010.01.011
- * regarding spatio-temporal filter and the bigger retina model :
- * Vision: Images, Signals and Neural Networks: Models of Neural Processing in Visual Perception (Progress in Neural Processing),By: Jeanny Herault, ISBN: 9814273686. WAPI (Tower ID): 113266891.
- */
+//! @addtogroup bioinspired
+//! @{
+
+/** @brief  a wrapper class which allows the tone mapping algorithm of Meylan&al(2007) to be used with OpenCV.
+
+This algorithm is already implemented in thre Retina class (retina::applyFastToneMapping) but used it does not require all the retina model to be allocated. This allows a light memory use for low memory devices (smartphones, etc.
+As a summary, these are the model properties:
+- 2 stages of local luminance adaptation with a different local neighborhood for each.
+- first stage models the retina photorecetors local luminance adaptation
+- second stage models th ganglion cells local information adaptation
+- compared to the initial publication, this class uses spatio-temporal low pass filters instead of spatial only filters.
+  this can help noise robustness and temporal stability for video sequence use cases.
+
+for more information, read to the following papers :
+Meylan L., Alleysson D., and Susstrunk S., A Model of Retinal Local Adaptation for the Tone Mapping of Color Filter Array Images, Journal of Optical Society of America, A, Vol. 24, N 9, September, 1st, 2007, pp. 2807-2816Benoit A., Caplier A., Durette B., Herault, J., "USING HUMAN VISUAL SYSTEM MODELING FOR BIO-INSPIRED LOW LEVEL IMAGE PROCESSING", Elsevier, Computer Vision and Image Understanding 114 (2010), pp. 758-773, DOI: http://dx.doi.org/10.1016/j.cviu.2010.01.011
+regarding spatio-temporal filter and the bigger retina model :
+Vision: Images, Signals and Neural Networks: Models of Neural Processing in Visual Perception (Progress in Neural Processing),By: Jeanny Herault, ISBN: 9814273686. WAPI (Tower ID): 113266891.
+*/
 class CV_EXPORTS_W RetinaFastToneMapping : public Algorithm
 {
 public:
 
-    /**
-     * method that applies a luminance correction (initially High Dynamic Range (HDR) tone mapping) using only the 2 local adaptation stages of the retina parvocellular channel : photoreceptors level and ganlion cells level. Spatio temporal filtering is applied but limited to temporal smoothing and eventually high frequencies attenuation. This is a lighter method than the one available using the regular retina::run method. It is then faster but it does not include complete temporal filtering nor retina spectral whitening. Then, it can have a more limited effect on images with a very high dynamic range. This is an adptation of the original still image HDR tone mapping algorithm of David Alleyson, Sabine Susstruck and Laurence Meylan's work, please cite:
-    * -> Meylan L., Alleysson D., and Susstrunk S., A Model of Retinal Local Adaptation for the Tone Mapping of Color Filter Array Images, Journal of Optical Society of America, A, Vol. 24, N 9, September, 1st, 2007, pp. 2807-2816
-     @param inputImage the input image to process RGB or gray levels
-     @param outputToneMappedImage the output tone mapped image
-     */
+    /** @brief applies a luminance correction (initially High Dynamic Range (HDR) tone mapping)
+
+    using only the 2 local adaptation stages of the retina parvocellular channel : photoreceptors
+    level and ganlion cells level. Spatio temporal filtering is applied but limited to temporal
+    smoothing and eventually high frequencies attenuation. This is a lighter method than the one
+    available using the regular retina::run method. It is then faster but it does not include
+    complete temporal filtering nor retina spectral whitening. Then, it can have a more limited
+    effect on images with a very high dynamic range. This is an adptation of the original still
+    image HDR tone mapping algorithm of David Alleyson, Sabine Susstruck and Laurence Meylan's
+    work, please cite: -> Meylan L., Alleysson D., and Susstrunk S., A Model of Retinal Local
+    Adaptation for the Tone Mapping of Color Filter Array Images, Journal of Optical Society of
+    America, A, Vol. 24, N 9, September, 1st, 2007, pp. 2807-2816
+
+    @param inputImage the input image to process RGB or gray levels
+    @param outputToneMappedImage the output tone mapped image
+    */
     CV_WRAP virtual void applyFastToneMapping(InputArray inputImage, OutputArray outputToneMappedImage)=0;
 
-    /**
-     * setup method that updates tone mapping behaviors by adjusing the local luminance computation area
-     * @param photoreceptorsNeighborhoodRadius the first stage local adaptation area
-     * @param ganglioncellsNeighborhoodRadius the second stage local adaptation area
-     * @param meanLuminanceModulatorK the factor applied to modulate the meanLuminance information (default is 1, see reference paper)
+    /** @brief updates tone mapping behaviors by adjusing the local luminance computation area
+
+    @param photoreceptorsNeighborhoodRadius the first stage local adaptation area
+    @param ganglioncellsNeighborhoodRadius the second stage local adaptation area
+    @param meanLuminanceModulatorK the factor applied to modulate the meanLuminance information
+    (default is 1, see reference paper)
      */
     CV_WRAP virtual void setup(const float photoreceptorsNeighborhoodRadius=3.f, const float ganglioncellsNeighborhoodRadius=1.f, const float meanLuminanceModulatorK=1.f)=0;
 };
 
+//! @relates bioinspired::RetinaFastToneMapping
 CV_EXPORTS_W Ptr<RetinaFastToneMapping> createRetinaFastToneMapping(Size inputSize);
 
+//! @}
+
 }
 }
 #endif /* __OPENCV_BIOINSPIRED_RETINAFASTTONEMAPPING_HPP__ */

modules/ccalib/include/opencv2/ccalib.hpp

@@ -49,8 +49,14 @@
 
 #include <vector>
 
+/** @defgroup ccalib Custom Calibration Pattern for 3D reconstruction
+*/
+
 namespace cv{ namespace ccalib{
 
+//! @addtogroup ccalib
+//! @{
+
 class CV_EXPORTS CustomPattern : public Algorithm
 {
 public:
@@ -66,11 +72,11 @@ public:
 	bool isInitialized();
 
 	void getPatternPoints(OutputArray original_points);
-	/*
+    /**<
 		Returns a vector<Point> of the original points.
 	*/
 	double getPixelSize();
-	/*
+    /**<
 		Get the pixel size of the pattern
 	*/
 
@@ -86,7 +92,7 @@ public:
 				Size imageSize, InputOutputArray cameraMatrix, InputOutputArray distCoeffs,
 				OutputArrayOfArrays rvecs, OutputArrayOfArrays tvecs, int flags = 0,
 				TermCriteria criteria = TermCriteria(TermCriteria::COUNT + TermCriteria::EPS, 30, DBL_EPSILON));
-	/*
+    /**<
 		Calls the calirateCamera function with the same inputs.
 	*/
 
@@ -94,7 +100,7 @@ public:
                 OutputArray rvec, OutputArray tvec, bool useExtrinsicGuess = false, int flags = SOLVEPNP_ITERATIVE);
 	bool findRt(InputArray image, InputArray cameraMatrix, InputArray distCoeffs,
                 OutputArray rvec, OutputArray tvec, bool useExtrinsicGuess = false, int flags = SOLVEPNP_ITERATIVE);
-	/*
+    /**<
 		Uses solvePnP to find the rotation and translation of the pattern
 		with respect to the camera frame.
 	*/
@@ -105,13 +111,13 @@ public:
 	bool findRtRANSAC(InputArray image, InputArray cameraMatrix, InputArray distCoeffs,
 				OutputArray rvec, OutputArray tvec, bool useExtrinsicGuess = false, int iterationsCount = 100,
 				float reprojectionError = 8.0, int minInliersCount = 100, OutputArray inliers = noArray(), int flags = SOLVEPNP_ITERATIVE);
-        /*
+        /**<
 		Uses solvePnPRansac()
 	*/
 
 	void drawOrientation(InputOutputArray image, InputArray tvec, InputArray rvec, InputArray cameraMatrix,
 						 InputArray distCoeffs, double axis_length = 3, int axis_width = 2);
-	/*
+    /**<
 		pattern_corners -> projected over the image position of the edges of the pattern.
 	*/
 
@@ -144,6 +150,8 @@ private:
 	void refineKeypointsPos(const Mat& img, std::vector<KeyPoint>& kp);
 };
 
+//! @}
+
 }} // namespace ccalib, cv
 
 #endif

modules/cvv/doc/cvv.rst

@@ -7,5 +7,5 @@ The module provides an interactive GUI to debug and incrementally design compute
 .. toctree::
     :maxdepth: 2
 
-    CVV API Documentation <cvv_api/index>
-    CVV GUI Documentation <cvv_gui/index>
+    CVV API Documentation <cvv_api>
+    CVV GUI Documentation <cvv_gui>

modules/cvv/include/opencv2/cvv/call_meta_data.hpp

@@ -7,6 +7,10 @@
 
 namespace cvv
 {
+
+//! @addtogroup cvv
+//! @{
+
 namespace impl
 {
 
@@ -49,6 +53,9 @@ struct CallMetaData
 	const bool isKnown;
 };
 }
+
+//! @}
+
 } // namespaces
 
 #ifdef __GNUC__

modules/cvv/include/opencv2/cvv/cvv.hpp

+/**
+@defgroup cvv GUI for Interactive Visual Debugging of Computer Vision Programs
+
+Namespace for all functions is **cvv**, i.e. *cvv::showImage()*.
+
+Compilation:
+
+-   For development, i.e. for cvv GUI to show up, compile your code using cvv with
+    *g++ -DCVVISUAL_DEBUGMODE*.
+-   For release, i.e. cvv calls doing nothing, compile your code without above flag.
+
+See cvv tutorial for a commented example application using cvv.
+
+*/
+
 #include <opencv2/cvv/call_meta_data.hpp>
 #include <opencv2/cvv/debug_mode.hpp>
 #include <opencv2/cvv/dmatch.hpp>
 #include <opencv2/cvv/filter.hpp>
 #include <opencv2/cvv/final_show.hpp>
 #include <opencv2/cvv/show_image.hpp>
+

modules/cvv/include/opencv2/cvv/debug_mode.hpp

@@ -10,6 +10,9 @@
 namespace cvv
 {
 
+//! @addtogroup cvv
+//! @{
+
 namespace impl
 {
 
@@ -24,22 +27,25 @@ static inline bool &getDebugFlag()
 
 } // namespace impl
 
-/**
- * @brief Returns whether debug-mode is active for this TU and thread.
- */
+/** @brief Returns whether debug-mode is active for this TU and thread.
+*/
 static inline bool debugMode()
 {
 	return impl::getDebugFlag();
 }
 
-/**
- * @brief Set the debug-mode for this TU and thread.
+/** @brief Enable or disable cvv for current translation unit and thread
+
+(disabled this way has higher - but still low - overhead compared to using the compile flags).
+@param active
  */
 static inline void setDebugFlag(bool active)
 {
 	impl::getDebugFlag() = active;
 }
 
+//! @}
+
 } // namespace cvv
 
 #endif

modules/cvv/include/opencv2/cvv/dmatch.hpp

@@ -9,9 +9,16 @@
 #include "call_meta_data.hpp"
 #include "debug_mode.hpp"
 
+#ifdef CV_DOXYGEN
+#define CVVISUAL_DEBUGMODE
+#endif
+
 namespace cvv
 {
 
+//! @addtogroup cvv
+//! @{
+
 namespace impl
 {
 void debugDMatch(cv::InputArray img1, std::vector<cv::KeyPoint> keypoints1,
@@ -22,6 +29,22 @@ void debugDMatch(cv::InputArray img1, std::vector<cv::KeyPoint> keypoints1,
 } // namespace impl
 
 #ifdef CVVISUAL_DEBUGMODE
+/** @brief Add a filled in DMatch \<dmatch\> to debug GUI.
+
+The matches can are visualized for interactive inspection in different GUI views (one similar to an
+interactive :draw_matches:drawMatches\<\>).
+
+@param img1 First image used in DMatch \<dmatch\>.
+@param keypoints1 Keypoints of first image.
+@param img2 Second image used in DMatch.
+@param keypoints2 Keypoints of second image.
+@param matches
+@param data See showImage
+@param description See showImage
+@param view See showImage
+@param useTrainDescriptor Use DMatch \<dmatch\>'s train descriptor index instead of query
+descriptor index.
+ */
 static inline void
 debugDMatch(cv::InputArray img1, std::vector<cv::KeyPoint> keypoints1,
             cv::InputArray img2, std::vector<cv::KeyPoint> keypoints2,
@@ -36,6 +59,7 @@ debugDMatch(cv::InputArray img1, std::vector<cv::KeyPoint> keypoints1,
 		                  data, description, view, useTrainDescriptor);
 	}
 }
+/** @overload */
 static inline void
 debugDMatch(cv::InputArray img1, std::vector<cv::KeyPoint> keypoints1,
             cv::InputArray img2, std::vector<cv::KeyPoint> keypoints2,
@@ -52,9 +76,6 @@ debugDMatch(cv::InputArray img1, std::vector<cv::KeyPoint> keypoints1,
 	}
 }
 #else
-/**
- * @brief Debug a set of matches between two images.
- */
 static inline void debugDMatch(cv::InputArray, std::vector<cv::KeyPoint>,
                                cv::InputArray, std::vector<cv::KeyPoint>,
                                std::vector<cv::DMatch>,
@@ -63,9 +84,6 @@ static inline void debugDMatch(cv::InputArray, std::vector<cv::KeyPoint>,
                                bool = true)
 {
 }
-/**
- * Dito.
- */
 static inline void debugDMatch(cv::InputArray, std::vector<cv::KeyPoint>,
                                cv::InputArray, std::vector<cv::KeyPoint>,
                                std::vector<cv::DMatch>,
@@ -75,6 +93,8 @@ static inline void debugDMatch(cv::InputArray, std::vector<cv::KeyPoint>,
 }
 #endif
 
+//! @}
+
 } // namespace cvv
 
 #endif

modules/cvv/include/opencv2/cvv/filter.hpp

@@ -8,9 +8,16 @@
 #include "call_meta_data.hpp"
 #include "debug_mode.hpp"
 
+#ifdef CV_DOXYGEN
+#define CVVISUAL_DEBUGMODE
+#endif
+
 namespace cvv
 {
 
+//! @addtogroup cvv
+//! @{
+
 namespace impl
 {
 // implementation outside API
@@ -20,6 +27,11 @@ void debugFilter(cv::InputArray original, cv::InputArray result,
 } // namespace impl
 
 #ifdef CVVISUAL_DEBUGMODE
+/**
+ * @brief Use the debug-framework to compare two images (from which the second
+ * is intended to be the result of
+ * a filter applied to the first).
+ */
 static inline void
 debugFilter(cv::InputArray original, cv::InputArray result,
             impl::CallMetaData metaData = impl::CallMetaData(),
@@ -31,6 +43,7 @@ debugFilter(cv::InputArray original, cv::InputArray result,
 		                  view);
 	}
 }
+/** @overload */
 static inline void debugFilter(cv::InputArray original, cv::InputArray result,
                                impl::CallMetaData metaData,
                                const ::std::string &description,
@@ -43,20 +56,12 @@ static inline void debugFilter(cv::InputArray original, cv::InputArray result,
 	}
 }
 #else
-/**
- * @brief Use the debug-framework to compare two images (from which the second
- * is intended to be the result of
- * a filter applied to the first).
- */
 static inline void debugFilter(cv::InputArray, cv::InputArray,
                                impl::CallMetaData = impl::CallMetaData(),
                                const char * = nullptr, const char * = nullptr)
 {
 }
 
-/**
- * Dito.
- */
 static inline void debugFilter(cv::InputArray, cv::InputArray,
                                impl::CallMetaData, const ::std::string &,
                                const ::std::string &)
@@ -64,6 +69,8 @@ static inline void debugFilter(cv::InputArray, cv::InputArray,
 }
 #endif
 
+//! @}
+
 } // namespace cvv
 
 #endif

modules/cvv/include/opencv2/cvv/final_show.hpp

@@ -6,22 +6,18 @@
 namespace cvv
 {
 
+//! @addtogroup cvv
+//! @{
+
 namespace impl
 {
 void finalShow();
 }
 
-/**
- * @brief Passes the control to the debug-window for a last time.
- *
- * This function must be called once if there was any prior debug-call. After that all debug-data
- * are freed.
- *
- * If there was no prior call it may be called once in which case it returns
- * without opening a window.
- *
- * In either case no further debug-calls must be made (undefined behaviour!!).
- *
+/** @brief Passes the control to the debug-window for a last time.
+
+This function **must** be called *once* *after* all cvv calls if any. As an alternative create an
+instance of FinalShowCaller, which calls finalShow() in its destructor (RAII-style).
  */
 inline void finalShow()
 {
@@ -48,6 +44,8 @@ public:
 	}
 };
 
+//! @}
+
 }
 
 #endif

modules/cvv/include/opencv2/cvv/show_image.hpp

@@ -8,9 +8,16 @@
 #include "call_meta_data.hpp"
 #include "debug_mode.hpp"
 
+#ifdef CV_DOXYGEN
+#define CVVISUAL_DEBUGMODE
+#endif
+
 namespace cvv
 {
 
+//! @addtogroup cvv
+//! @{
+
 namespace impl
 {
 // implementation outside API
@@ -19,6 +26,15 @@ void showImage(cv::InputArray img, const CallMetaData &data,
 } // namespace impl
 
 #ifdef CVVISUAL_DEBUGMODE
+/** @brief Add a single image to debug GUI (similar to imshow \<\>).
+
+@param img Image to show in debug GUI.
+@param metaData Properly initialized CallMetaData struct, i.e. information about file, line and
+function name for GUI. Use CVVISUAL_LOCATION macro.
+@param description Human readable description to provide context to image.
+@param view Preselect view that will be used to visualize this image in GUI. Other views can still
+be selected in GUI later on.
+ */
 static inline void showImage(cv::InputArray img,
                              impl::CallMetaData metaData = impl::CallMetaData(),
                              const char *description = nullptr,
@@ -29,6 +45,7 @@ static inline void showImage(cv::InputArray img,
 		impl::showImage(img, metaData, description, view);
 	}
 }
+/** @overload */
 static inline void showImage(cv::InputArray img, impl::CallMetaData metaData,
                              const ::std::string &description,
                              const ::std::string &view = "")
@@ -40,23 +57,19 @@ static inline void showImage(cv::InputArray img, impl::CallMetaData metaData,
 	}
 }
 #else
-/**
- * Use the debug-framework to show a single image.
- */
 static inline void showImage(cv::InputArray,
                              impl::CallMetaData = impl::CallMetaData(),
                              const char * = nullptr, const char * = nullptr)
 {
 }
-/**
- * Dito.
- */
 static inline void showImage(cv::InputArray, impl::CallMetaData,
                              const ::std::string &, const ::std::string &)
 {
 }
 #endif
 
+//! @}
+
 } // namespace cvv
 
 #endif

modules/datasets/doc/datasets.rst

@@ -15,105 +15,105 @@ It is planned to have:
 .. toctree::
     :hidden:
 
-    datasets/ar_hmdb
-    datasets/ar_sports
-    datasets/fr_adience
-    datasets/fr_lfw
-    datasets/gr_chalearn
-    datasets/gr_skig
-    datasets/hpe_humaneva
-    datasets/hpe_parse
-    datasets/ir_affine
-    datasets/ir_robot
-    datasets/is_bsds
-    datasets/is_weizmann
-    datasets/msm_epfl
-    datasets/msm_middlebury
-    datasets/or_imagenet
-    datasets/or_mnist
-    datasets/or_sun
-    datasets/pd_caltech
-    datasets/slam_kitti
-    datasets/slam_tumindoor
-    datasets/tr_chars
-    datasets/tr_svt
+    ar_hmdb
+    ar_sports
+    fr_adience
+    fr_lfw
+    gr_chalearn
+    gr_skig
+    hpe_humaneva
+    hpe_parse
+    ir_affine
+    ir_robot
+    is_bsds
+    is_weizmann
+    msm_epfl
+    msm_middlebury
+    or_imagenet
+    or_mnist
+    or_sun
+    pd_caltech
+    slam_kitti
+    slam_tumindoor
+    tr_chars
+    tr_svt
 
 Action Recognition
 ------------------
 
-    :doc:`datasets/ar_hmdb` [#f1]_
+    :doc:`ar_hmdb` [#f1]_
 
-    :doc:`datasets/ar_sports`
+    :doc:`ar_sports`
 
 Face Recognition
 ----------------
 
-    :doc:`datasets/fr_adience`
+    :doc:`fr_adience`
 
-    :doc:`datasets/fr_lfw` [#f1]_
+    :doc:`fr_lfw` [#f1]_
 
 Gesture Recognition
 -------------------
 
-    :doc:`datasets/gr_chalearn`
+    :doc:`gr_chalearn`
 
-    :doc:`datasets/gr_skig`
+    :doc:`gr_skig`
 
 Human Pose Estimation
 ---------------------
 
-    :doc:`datasets/hpe_humaneva`
+    :doc:`hpe_humaneva`
 
-    :doc:`datasets/hpe_parse`
+    :doc:`hpe_parse`
 
 Image Registration
 ------------------
 
-    :doc:`datasets/ir_affine`
+    :doc:`ir_affine`
 
-    :doc:`datasets/ir_robot`
+    :doc:`ir_robot`
 
 Image Segmentation
 ------------------
 
-    :doc:`datasets/is_bsds`
+    :doc:`is_bsds`
 
-    :doc:`datasets/is_weizmann`
+    :doc:`is_weizmann`
 
 Multiview Stereo Matching
 -------------------------
 
-    :doc:`datasets/msm_epfl`
+    :doc:`msm_epfl`
 
-    :doc:`datasets/msm_middlebury`
+    :doc:`msm_middlebury`
 
 Object Recognition
 ------------------
 
-    :doc:`datasets/or_imagenet`
+    :doc:`or_imagenet`
 
-    :doc:`datasets/or_mnist` [#f2]_
+    :doc:`or_mnist` [#f2]_
 
-    :doc:`datasets/or_sun`
+    :doc:`or_sun`
 
 Pedestrian Detection
 --------------------
 
-    :doc:`datasets/pd_caltech` [#f2]_
+    :doc:`pd_caltech` [#f2]_
 
 SLAM
 ----
 
-    :doc:`datasets/slam_kitti`
+    :doc:`slam_kitti`
 
-    :doc:`datasets/slam_tumindoor`
+    :doc:`slam_tumindoor`
 
 Text Recognition
 ----------------
 
-    :doc:`datasets/tr_chars`
+    :doc:`tr_chars`
 
-    :doc:`datasets/tr_svt` [#f1]_
+    :doc:`tr_svt` [#f1]_
 
 *Footnotes*
 

modules/datasets/include/opencv2/datasets/ar_hmdb.hpp

@@ -54,6 +54,9 @@ namespace cv
 namespace datasets
 {
 
+//! @addtogroup datasets_ar
+//! @{
+
 struct AR_hmdbObj : public Object
 {
     int id;
@@ -69,6 +72,8 @@ public:
     static Ptr<AR_hmdb> create();
 };
 
+//! @}
+
 }
 }
 

modules/datasets/include/opencv2/datasets/ar_sports.hpp

@@ -54,6 +54,9 @@ namespace cv
 namespace datasets
 {
 
+//! @addtogroup datasets_ar
+//! @{
+
 struct AR_sportsObj : public Object
 {
     std::string videoUrl;
@@ -68,6 +71,8 @@ public:
     static Ptr<AR_sports> create();
 };
 
+//! @}
+
 }
 }
 

modules/datasets/include/opencv2/datasets/fr_adience.hpp

@@ -54,6 +54,9 @@ namespace cv
 namespace datasets
 {
 
+//! @addtogroup datasets_fr
+//! @{
+
 enum genderType
 {
     male = 0,
@@ -87,6 +90,8 @@ public:
     std::vector<std::string> paths;
 };
 
+//! @}
+
 }
 }
 

modules/datasets/include/opencv2/datasets/fr_lfw.hpp

@@ -54,6 +54,9 @@ namespace cv
 namespace datasets
 {
 
+//! @addtogroup datasets_fr
+//! @{
+
 struct FR_lfwObj : public Object
 {
     std::string image1, image2;
@@ -68,6 +71,8 @@ public:
     static Ptr<FR_lfw> create();
 };
 
+//! @}
+
 }
 }
 

modules/datasets/include/opencv2/datasets/gr_chalearn.hpp

@@ -54,6 +54,9 @@ namespace cv
 namespace datasets
 {
 
+//! @addtogroup datasets_gr
+//! @{
+
 struct groundTruth
 {
     int gestureID, initialFrame, lastFrame;
@@ -85,6 +88,8 @@ public:
     static Ptr<GR_chalearn> create();
 };
 
+//! @}
+
 }
 }
 

modules/datasets/include/opencv2/datasets/gr_skig.hpp

@@ -54,6 +54,9 @@ namespace cv
 namespace datasets
 {
 
+//! @addtogroup datasets_gr
+//! @{
+
 enum actionType
 {
     circle = 1,
@@ -107,6 +110,8 @@ public:
     static Ptr<GR_skig> create();
 };
 
+//! @}
+
 }
 }
 

modules/datasets/include/opencv2/datasets/hpe_humaneva.hpp

@@ -54,6 +54,9 @@ namespace cv
 namespace datasets
 {
 
+//! @addtogroup datasets_hpe
+//! @{
+
 struct HPE_humanevaObj : public Object
 {
     char person; // 1..4
@@ -79,6 +82,8 @@ public:
     static Ptr<HPE_humaneva> create(int num=humaneva_1);
 };
 
+//! @}
+
 }
 }
 

modules/datasets/include/opencv2/datasets/hpe_parse.hpp

@@ -54,6 +54,9 @@ namespace cv
 namespace datasets
 {
 
+//! @addtogroup datasets_hpe
+//! @{
+
 struct HPE_parseObj : public Object
 {
     std::string name;
@@ -67,6 +70,8 @@ public:
     static Ptr<HPE_parse> create();
 };
 
+//! @}
+
 }
 }
 

modules/datasets/include/opencv2/datasets/ir_affine.hpp

@@ -55,6 +55,9 @@ namespace cv
 namespace datasets
 {
 
+//! @addtogroup datasets_ir
+//! @{
+
 struct IR_affineObj : public Object
 {
     std::string imageName;
@@ -69,6 +72,8 @@ public:
     static Ptr<IR_affine> create();
 };
 
+//! @}
+
 }
 }
 

modules/datasets/include/opencv2/datasets/ir_robot.hpp

@@ -54,6 +54,9 @@ namespace cv
 namespace datasets
 {
 
+//! @addtogroup datasets_ir
+//! @{
+
 // calibration matrix from calibrationFile.mat
 // 2.8290e+03   0.0000e+00   8.0279e+02
 // 0.0000e+00   2.8285e+03   6.1618e+02
@@ -78,6 +81,8 @@ public:
     static Ptr<IR_robot> create();
 };
 
+//! @}
+
 }
 }
 

modules/datasets/include/opencv2/datasets/is_bsds.hpp

@@ -54,6 +54,9 @@ namespace cv
 namespace datasets
 {
 
+//! @addtogroup datasets_is
+//! @{
+
 struct IS_bsdsObj : public Object
 {
     std::string name;
@@ -67,6 +70,8 @@ public:
     static Ptr<IS_bsds> create();
 };
 
+//! @}
+
 }
 }
 

modules/datasets/include/opencv2/datasets/is_weizmann.hpp

@@ -54,6 +54,9 @@ namespace cv
 namespace datasets
 {
 
+//! @addtogroup datasets_is
+//! @{
+
 struct IS_weizmannObj : public Object
 {
     std::string imageName;
@@ -70,6 +73,8 @@ public:
     static Ptr<IS_weizmann> create();
 };
 
+//! @}
+
 }
 }
 

modules/datasets/include/opencv2/datasets/msm_epfl.hpp

@@ -54,6 +54,9 @@ namespace cv
 namespace datasets
 {
 
+//! @addtogroup datasets_msm
+//! @{
+
 struct cameraParam
 {
     Matx33d mat1;
@@ -79,6 +82,8 @@ public:
     static Ptr<MSM_epfl> create();
 };
 
+//! @}
+
 }
 }
 

modules/datasets/include/opencv2/datasets/msm_middlebury.hpp

@@ -54,6 +54,9 @@ namespace cv
 namespace datasets
 {
 
+//! @addtogroup datasets_msm
+//! @{
+
 struct MSM_middleburyObj : public Object
 {
     std::string imageName;
@@ -70,6 +73,8 @@ public:
     static Ptr<MSM_middlebury> create();
 };
 
+//! @}
+
 }
 }
 

modules/datasets/include/opencv2/datasets/or_imagenet.hpp

@@ -54,6 +54,9 @@ namespace cv
 namespace datasets
 {
 
+//! @addtogroup datasets_or
+//! @{
+
 struct OR_imagenetObj : public Object
 {
     int id;
@@ -68,6 +71,8 @@ public:
     static Ptr<OR_imagenet> create();
 };
 
+//! @}
+
 }
 }
 

modules/datasets/include/opencv2/datasets/or_mnist.hpp

@@ -54,6 +54,9 @@ namespace cv
 namespace datasets
 {
 
+//! @addtogroup datasets_or
+//! @{
+
 struct OR_mnistObj : public Object
 {
     char label; // 0..9
@@ -68,6 +71,8 @@ public:
     static Ptr<OR_mnist> create();
 };
 
+//! @}
+
 }
 }
 

modules/datasets/include/opencv2/datasets/or_sun.hpp

@@ -54,6 +54,9 @@ namespace cv
 namespace datasets
 {
 
+//! @addtogroup datasets_or
+//! @{
+
 struct OR_sunObj : public Object
 {
     int label;
@@ -70,6 +73,8 @@ public:
     std::vector<std::string> paths;
 };
 
+//! @}
+
 }
 }
 

modules/datasets/include/opencv2/datasets/pd_caltech.hpp

@@ -54,6 +54,9 @@ namespace cv
 namespace datasets
 {
 
+//! @addtogroup datasets_pd
+//! @{
+
 struct PD_caltechObj : public Object
 {
     //double groundTrue[][];
@@ -78,6 +81,8 @@ public:
     static Ptr<PD_caltech> create();
 };
 
+//! @}
+
 }
 }
 

modules/datasets/include/opencv2/datasets/slam_kitti.hpp

@@ -54,6 +54,9 @@ namespace cv
 namespace datasets
 {
 
+//! @addtogroup datasets_slam
+//! @{
+
 struct pose
 {
     double elem[12];
@@ -76,6 +79,8 @@ public:
     static Ptr<SLAM_kitti> create();
 };
 
+//! @}
+
 }
 }
 

modules/datasets/include/opencv2/datasets/slam_tumindoor.hpp

@@ -54,6 +54,9 @@ namespace cv
 namespace datasets
 {
 
+//! @addtogroup datasets_slam
+//! @{
+
 enum imageType
 {
     LEFT = 0,
@@ -76,6 +79,8 @@ public:
     static Ptr<SLAM_tumindoor> create();
 };
 
+//! @}
+
 }
 }
 

modules/datasets/include/opencv2/datasets/tr_chars.hpp

@@ -54,6 +54,9 @@ namespace cv
 namespace datasets
 {
 
+//! @addtogroup datasets_tr
+//! @{
+
 struct TR_charsObj : public Object
 {
     std::string imgName;
@@ -68,6 +71,8 @@ public:
     static Ptr<TR_chars> create();
 };
 
+//! @}
+
 }
 }
 

modules/datasets/include/opencv2/datasets/tr_svt.hpp

@@ -54,6 +54,9 @@ namespace cv
 namespace datasets
 {
 
+//! @addtogroup datasets_tr
+//! @{
+
 struct tag
 {
     std::string value;
@@ -75,6 +78,8 @@ public:
     static Ptr<TR_svt> create();
 };
 
+//! @}
+
 }
 }
 

modules/datasets/include/opencv2/datasets/util.hpp

@@ -57,12 +57,17 @@ namespace cv
 namespace datasets
 {
 
+//! @addtogroup datasets
+//! @{
+
 void CV_EXPORTS split(const std::string &s, std::vector<std::string> &elems, char delim);
 
 void CV_EXPORTS createDirectory(const std::string &path);
 
 void CV_EXPORTS getDirList(const std::string &dirName, std::vector<std::string> &fileNames);
 
+//! @}
+
 }
 }
 

modules/face/doc/changelog.markdown

+Face module changelog {#face_changelog}
+=====================
+
+Release 0.05
+------------
+
+This library is now included in the official OpenCV distribution (from 2.4 on). The
+cv::FaceRecognizer is now an Algorithm, which better fits into the overall OpenCV API.
+
+To reduce the confusion on user side and minimize my work, libfacerec and OpenCV have been
+synchronized and are now based on the same interfaces and implementation.
+
+The library now has an extensive documentation:
+
+-   The API is explained in detail and with a lot of code examples.
+-   The face recognition guide I had written for Python and GNU Octave/MATLAB has been adapted to
+    the new OpenCV C++ cv::FaceRecognizer.
+-   A tutorial for gender classification with Fisherfaces.
+-   A tutorial for face recognition in videos (e.g. webcam).
+
+### Release highlights
+
+-   There are no single highlights to pick from, this release is a highlight itself.
+
+Release 0.04
+------------
+
+This version is fully Windows-compatible and works with OpenCV 2.3.1. Several bugfixes, but none
+influenced the recognition rate.
+
+### Release highlights
+
+-   A whole lot of exceptions with meaningful error messages.
+-   A tutorial for Windows users:
+    [<http://bytefish.de/blog/opencv_visual_studio_and_libfacerec>](http://bytefish.de/blog/opencv_visual_studio_and_libfacerec)
+
+Release 0.03
+------------
+
+Reworked the library to provide separate implementations in cpp files, because it's the preferred
+way of contributing OpenCV libraries. This means the library is not header-only anymore. Slight API
+changes were done, please see the documentation for details.
+
+### Release highlights
+
+-   New Unit Tests (for LBP Histograms) make the library more robust.
+-   Added more documentation.
+
+Release 0.02
+------------
+
+Reworked the library to provide separate implementations in cpp files, because it's the preferred
+way of contributing OpenCV libraries. This means the library is not header-only anymore. Slight API
+changes were done, please see the documentation for details.
+
+### Release highlights
+
+-   New Unit Tests (for LBP Histograms) make the library more robust.
+-   Added a documentation and changelog in reStructuredText.
+
+Release 0.01
+------------
+
+Initial release as header-only library.
+
+### Release highlights
+
+-   Colormaps for OpenCV to enhance the visualization.
+-   Face Recognition algorithms implemented:
+    -   Eigenfaces @cite TP91
+    -   Fisherfaces @cite BHK97
+    -   Local Binary Patterns Histograms @cite AHP04
+-   Added persistence facilities to store the models with a common API.
+-   Unit Tests (using [gtest](http://code.google.com/p/googletest/)).
+-   Providing a CMakeLists.txt to enable easy cross-platform building.

modules/face/doc/face.bib

+@incollection{AHP04,
+  title={Face recognition with local binary patterns},
+  author={Ahonen, Timo and Hadid, Abdenour and Pietik{\"a}inen, Matti},
+  booktitle={Computer vision-eccv 2004},
+  pages={469--481},
+  year={2004},
+  publisher={Springer}
+}
+
+@article{BHK97,
+  title={Eigenfaces vs. fisherfaces: Recognition using class specific linear projection},
+  author={Belhumeur, Peter N. and Hespanha, Jo{\~a}o P and Kriegman, David},
+  journal={Pattern Analysis and Machine Intelligence, IEEE Transactions on},
+  volume={19},
+  number={7},
+  pages={711--720},
+  year={1997},
+  publisher={IEEE}
+}
+
+@inproceedings{Bru92,
+  title={Face recognition through geometrical features},
+  author={Brunelli, Roberto and Poggio, Tomaso},
+  booktitle={Computer Vision—ECCV'92},
+  pages={792--800},
+  year={1992},
+  organization={Springer}
+}
+
+@book{Duda01,
+  title={Pattern classification},
+  author={Duda, Richard O and Hart, Peter E and Stork, David G},
+  year={2012},
+  publisher={John Wiley \& Sons}
+}
+
+@article{Fisher36,
+  title={The use of multiple measurements in taxonomic problems},
+  author={Fisher, Ronald A},
+  journal={Annals of eugenics},
+  volume={7},
+  number={2},
+  pages={179--188},
+  year={1936},
+  publisher={Wiley Online Library}
+}
+
+@article{GBK01,
+  title={From few to many: Illumination cone models for face recognition under variable lighting and pose},
+  author={Georghiades, Athinodoros S. and Belhumeur, Peter N. and Kriegman, David},
+  journal={Pattern Analysis and Machine Intelligence, IEEE Transactions on},
+  volume={23},
+  number={6},
+  pages={643--660},
+  year={2001},
+  publisher={IEEE}
+}
+
+@article{Kanade73,
+  title={Picture processing system by computer complex and recognition of human faces},
+  author={Kanade, Takeo},
+  year={1974}
+}
+
+@article{KM01,
+  title={Pca versus lda},
+  author={Mart{\'\i}nez, Aleix M and Kak, Avinash C},
+  journal={Pattern Analysis and Machine Intelligence, IEEE Transactions on},
+  volume={23},
+  number={2},
+  pages={228--233},
+  year={2001},
+  publisher={IEEE}
+}
+
+@article{Lee05,
+  title={Acquiring linear subspaces for face recognition under variable lighting},
+  author={Lee, Kuang-Chih and Ho, Jeffrey and Kriegman, David},
+  journal={Pattern Analysis and Machine Intelligence, IEEE Transactions on},
+  volume={27},
+  number={5},
+  pages={684--698},
+  year={2005},
+  publisher={IEEE}
+}
+
+@incollection{Messer06,
+  title={Performance characterisation of face recognition algorithms and their sensitivity to severe illumination changes},
+  author={Messer, Kieron and Kittler, Josef and Short, James and Heusch, Guillaume and Cardinaux, Fabien and Marcel, Sebastien and Rodriguez, Yann and Shan, Shiguang and Su, Yu and Gao, Wen and others},
+  booktitle={Advances in Biometrics},
+  pages={1--11},
+  year={2005},
+  publisher={Springer}
+}
+
+@article{RJ91,
+  title={Small sample size effects in statistical pattern recognition: Recommendations for practitioners},
+  author={Raudys, Sarunas J and Jain, Anil K.},
+  journal={IEEE Transactions on pattern analysis and machine intelligence},
+  volume={13},
+  number={3},
+  pages={252--264},
+  year={1991},
+  publisher={IEEE Computer Society}
+}
+
+@article{Tan10,
+  title={Enhanced local texture feature sets for face recognition under difficult lighting conditions},
+  author={Tan, Xiaoyang and Triggs, Bill},
+  journal={Image Processing, IEEE Transactions on},
+  volume={19},
+  number={6},
+  pages={1635--1650},
+  year={2010},
+  publisher={IEEE}
+}
+
+@article{TP91,
+  title={Eigenfaces for recognition},
+  author={Turk, Matthew and Pentland, Alex},
+  journal={Journal of cognitive neuroscience},
+  volume={3},
+  number={1},
+  pages={71--86},
+  year={1991},
+  publisher={MIT Press}
+}
+
+@article{Tu06,
+  title={Newborns' face recognition: Role of inner and outer facial features},
+  author={Turati, Chiara and Macchi Cassia, Viola and Simion, Francesca and Leo, Irene},
+  journal={Child development},
+  volume={77},
+  number={2},
+  pages={297--311},
+  year={2006},
+  publisher={Wiley Online Library}
+}
+
+@article{Wiskott97,
+  title={Face recognition by elastic bunch graph matching},
+  author={Wiskott, Laurenz and Fellous, J-M and Kuiger, N and Von Der Malsburg, Christoph},
+  journal={Pattern Analysis and Machine Intelligence, IEEE Transactions on},
+  volume={19},
+  number={7},
+  pages={775--779},
+  year={1997},
+  publisher={IEEE}
+}
+
+@article{Zhao03,
+  title={Face recognition: A literature survey},
+  author={Zhao, Wenyi and Chellappa, Rama and Phillips, P Jonathon and Rosenfeld, Azriel},
+  journal={Acm Computing Surveys (CSUR)},
+  volume={35},
+  number={4},
+  pages={399--458},
+  year={2003},
+  publisher={ACM}
+}

modules/face/doc/face.rst

@@ -7,4 +7,4 @@ The module contains some recently added functionality that has not been stabiliz
 .. toctree::
     :maxdepth: 2
 
-    FaceRecognizer Documentation <facerec/index>
+    FaceRecognizer Documentation <index>