In read function, check before if node is empty to avoid erasing default value in case of missing parameter.
Add getters/setters to complete cpp/java/python API (needed for Java Tests.)
fix warning due to double to float conversion in freak
Add BAD descriptor to xfeatures2d module
* Adding new BAD descriptor to xfeatures2d module
* Changing BAD name by TEBLID and using int threshold again for BEBLID
* Changing link to AKAZE tutorial and moved parameters initialization to ::create()
* Adding f suffixes to floating-point parameters and using arrays again
* Added BEBLID local feature descriptor
* Solved format problems, moved descriptor data to .hpp files and added BeblidSize enum
* Deleting guards from BEBLID parameter files
* Using int for the BeblidSize, using at<> to access matrix and releasing descriptors when no keypoints are detected.
* Added files from http://code.opencv.org/issues/1053
The code structure had to be changed because of the
features2d/xfeatures2d split and to avoid changing
multiple modules (gaussian_pyramid doesn't seem ready
for inclusion in the (x)imgproc module).
Except for changes related to this, the patches
remain unchanged, including the outdated
copyright notice at the top of the files.
* Hide Harris-Laplace implementation behind pimpl-creating wrapper.
* Add test for Harris-Laplace feature detector.
* Handle empty images in Harris-Laplace detector.
* Replace HarrisAffineFeatureDetector with more flexible AffineFeature2D
* collapse unnecessary HarrisLaplace class into HarrisLaplaceFeatureDetector
* fold DoG pyramid code into harris_laplace_detector.cpp
* tuck auxiliary functions for Harris-Laplace into anonymous namespace
* use mask to filter keypoints in Harris-Laplace detector
* remove unused value of differentiation scale from calcAffineAdaptation
* make descriptor copy in AffineFeature2D independent of the data type
* Document interface for Harris-Laplace and AffineFeature2D
* Make type conversions explicit and decorate float literals with f in HarrisLaplace and AffineFeature2D
* Replace usage of non-standard log2 in Harris-Laplace feature detector
* Fix virtual overload errors in AffineFeature2D
* Add basic tests for AffineFeature2D and fix what they uncover
* Make type conversions in Harris-Laplace feature detector explicit
* Change license header for Harris-Laplace detector and AffineFeature2D
* Use Matx for small matrices in AffineFeature2D
* Remove redundant attributes of Elliptic_KeyPoint
* Convert Matx22f to Matx22d for inverting in AffineFeature2D
Some applications only want to know if there are feature at specific
locations. To fit these needs the FAST approach is extended in
FASTForPointSet to recieve a vector of locations and calculates the FAST
response on these positions.
If it is below the threshold, it will be removed from the list.
