Squash all commits into single one.

modules/xfeatures2d/doc/xfeatures2d.bib

@@ -44,3 +44,23 @@
   year={2012},
   organization={Ieee}
 }
+
+@incollection{LUCID,
+  title={Locally uniform comparison image descriptor},
+  author={Ziegler, Andrew, Eric Christiansen, David Kriegman, and Serge J. Belongie}
+  booktitle={Advances in Neural Information Processing Systems}
+  pages={1--9}
+  year={2012}
+  publisher={NIPS}
+}
+
+@article{Tola10,
+  author = "E. Tola and V. Lepetit and P. Fua",
+  title = {{DAISY: An Efficient Dense Descriptor Applied to Wide Baseline Stereo}},
+  journal = "IEEE Transactions on Pattern Analysis and Machine Intelligence",
+  year = 2010,
+  month = "May",
+  pages = "815--830",
+  volume = "32",
+  number = "5"
+}

modules/xfeatures2d/include/opencv2/xfeatures2d.hpp

@@ -128,7 +128,110 @@ class CV_EXPORTS BriefDescriptorExtractor : public DescriptorExtractor
 public:
     static Ptr<BriefDescriptorExtractor> create( int bytes = 32 );
 };
-    
+
+/** @brief Class implementing the locally uniform comparison image descriptor, described in @cite LUCID
+
+An image descriptor that can be computed very fast, while being
+about as robust as, for example, SURF or BRIEF.
+ */
+class CV_EXPORTS LUCID : public DescriptorExtractor
+{
+public:
+    /**
+     * @param lucid_kernel kernel for descriptor construction, where 1=3x3, 2=5x5, 3=7x7 and so forth
+     * @param blur_kernel kernel for blurring image prior to descriptor construction, where 1=3x3, 2=5x5, 3=7x7 and so forth
+     */
+    static Ptr<LUCID> create(const int lucid_kernel, const int blur_kernel);
+};
+
+/** @brief Class implementing DAISY descriptor, described in @cite Tola10
+
+@param radius radius of the descriptor at the initial scale
+@param q_radius amount of radial range division quantity
+@param q_theta amount of angular range division quantity
+@param q_hist amount of gradient orientations range division quantity
+DAISY::ONLY_KEYS means to compute descriptors only for keypoints in the list (default) and
+DAISY::COMP_FULL will compute descriptors for all pixels in the given image
+@param norm choose descriptors normalization type, where
+DAISY::NRM_NONE will not do any normalization (default),
+DAISY::NRM_PARTIAL mean that histograms are normalized independently for L2 norm equal to 1.0,
+DAISY::NRM_FULL mean that descriptors are normalized for L2 norm equal to 1.0,
+DAISY::NRM_SIFT mean that descriptors are normalized for L2 norm equal to 1.0 but no individual one is bigger than 0.154 as in SIFT
+@param H optional 3x3 homography matrix used to warp the grid of daisy but sampling keypoints remains unwarped on image
+@param interpolation switch to disable interpolation for speed improvement at minor quality loss
+@param use_orientation sample patterns using keypoints orientation, disabled by default.
+
+ */
+class CV_EXPORTS DAISY : public DescriptorExtractor
+{
+public:
+    enum
+    {
+        NRM_NONE = 100, NRM_PARTIAL = 101, NRM_FULL = 102, NRM_SIFT = 103,
+    };
+    static Ptr<DAISY> create( float radius = 15, int q_radius = 3, int q_theta = 8,
+                int q_hist = 8, int norm = DAISY::NRM_NONE, InputArray H = noArray(),
+                bool interpolation = true, bool use_orientation = false );
+
+    /** @overload
+     * @param image image to extract descriptors
+     * @param keypoints of interest within image
+     * @param descriptors resulted descriptors array
+     */
+    virtual void compute( InputArray image, std::vector<KeyPoint>& keypoints, OutputArray descriptors ) = 0;
+
+    /** @overload
+     * @param image image to extract descriptors
+     * @param roi region of interest within image
+     * @param descriptors resulted descriptors array for roi image pixels
+     */
+    virtual void compute( InputArray image, Rect roi, OutputArray descriptors ) = 0;
+
+    /**@overload
+     * @param image image to extract descriptors
+     * @param descriptors resulted descriptors array for all image pixels
+     */
+    virtual void compute( InputArray image, OutputArray descriptors ) = 0;
+
+    /**
+     * @param y position y on image
+     * @param x position x on image
+     * @param orientation orientation on image (0->360)
+     * @param descriptor supplied array for descriptor storage
+     */
+    virtual void get_descriptor( double y, double x, int orientation, float* descriptor ) const = 0;
+
+    /**
+     * @param y position y on image
+     * @param x position x on image
+     * @param orientation orientation on image (0->360)
+     * @param H homography matrix for warped grid
+     * @param descriptor supplied array for descriptor storage
+     * @param get_descriptor true if descriptor was computed
+     */
+    virtual bool get_descriptor( double y, double x, int orientation, double* H, float* descriptor ) const = 0;
+
+    /**
+     * @param y position y on image
+     * @param x position x on image
+     * @param orientation orientation on image (0->360)
+     * @param descriptor supplied array for descriptor storage
+     */
+    virtual void get_unnormalized_descriptor( double y, double x, int orientation, float* descriptor ) const = 0;
+
+    /**
+     * @param y position y on image
+     * @param x position x on image
+     * @param orientation orientation on image (0->360)
+     * @param H homography matrix for warped grid
+     * @param descriptor supplied array for descriptor storage
+     * @param get_unnormalized_descriptor true if descriptor was computed
+     */
+    virtual bool get_unnormalized_descriptor( double y, double x, int orientation, double* H, float* descriptor ) const = 0;
+
+};
+
+
 //! @}
 
 }

modules/xfeatures2d/perf/perf_daisy.cpp

+#include "perf_precomp.hpp"
+
+using namespace std;
+using namespace cv;
+using namespace cv::xfeatures2d;
+using namespace perf;
+using std::tr1::make_tuple;
+using std::tr1::get;
+
+typedef perf::TestBaseWithParam<std::string> daisy;
+
+#define DAISY_IMAGES \
+    "cv/detectors_descriptors_evaluation/images_datasets/leuven/img1.png",\
+    "stitching/a3.png"
+
+PERF_TEST_P(daisy, extract, testing::Values(DAISY_IMAGES))
+{
+    string filename = getDataPath(GetParam());
+    Mat frame = imread(filename, IMREAD_GRAYSCALE);
+    ASSERT_FALSE(frame.empty()) << "Unable to load source image " << filename;
+
+    Mat mask;
+    declare.in(frame).time(90);
+
+    Ptr<DAISY> descriptor = DAISY::create();
+
+    vector<KeyPoint> points;
+    vector<float> descriptors;
+    // compute all daisies in image
+    TEST_CYCLE() descriptor->compute(frame, descriptors);
+
+    SANITY_CHECK(descriptors, 1e-4);
+}

modules/xfeatures2d/test/test_features2d.cpp

@@ -1010,6 +1010,13 @@ TEST( Features2d_DescriptorExtractor_SURF, regression )
     test.safe_run();
 }
 
+TEST( Features2d_DescriptorExtractor_DAISY, regression )
+{
+    CV_DescriptorExtractorTest<L2<float> > test( "descriptor-daisy",  0.05f,
+                                                DAISY::create() );
+    test.safe_run();
+}
+
 TEST( Features2d_DescriptorExtractor_FREAK, regression )
 {
     // TODO adjust the parameters below

modules/xfeatures2d/test/test_rotation_and_scale_invariance.cpp

@@ -651,6 +651,15 @@ TEST(Features2d_RotationInvariance_Descriptor_SIFT, regression)
     test.safe_run();
 }
 
+TEST(Features2d_RotationInvariance_Descriptor_DAISY, regression)
+{
+    DescriptorRotationInvarianceTest test(BRISK::create(),
+                                          DAISY::create(15, 3, 8, 8, DAISY::NRM_NONE, noArray(), true, true),
+                                          NORM_L1,
+                                          0.79f);
+    test.safe_run();
+}
+
 /*
  * Detector's scale invariance check
  */
@@ -708,3 +717,12 @@ TEST(Features2d_RotationInvariance2_Detector_SURF, regression)
     ASSERT_LT( fabs(keypoints[1].response - keypoints[3].response), 1e-6);
     ASSERT_LT( fabs(keypoints[1].response - keypoints[4].response), 1e-6);
 }
+
+TEST(Features2d_ScaleInvariance_Descriptor_DAISY, regression)
+{
+    DescriptorScaleInvarianceTest test(BRISK::create(),
+                                       DAISY::create(15, 3, 8, 8, DAISY::NRM_NONE, noArray(), true, true),
+                                       NORM_L1,
+                                       0.075f);
+    test.safe_run();
+}