- lowered memory usage (now the train use ~3x less memory)
- improved speed (removed some bottlenecks and added fast_log)
- added support to grayscale images
- the LUV features are not computed if the image is grayscale (leads to
an improved detection rate)
- added various parameters (limit_ps, limit_bg, alpha, slidingStep,
is_grayscale)
- added detect() function for a better control of the resize factor

Fix documentation title in TOF and some typos

cvv fix docs

Enabled java wrappers for bioinspired/retina module

Added Custom Calibration Pattern Module.

make opencv_cudaarithm dependency for xfeatures2d optional

Integrate cvv module: Interactive Visual Debugging of Computer Vision applications

datasets loading module: continue

Inpainting

Integration of SEEDS superpixel algorithm to opencv_contrib

fix mismatched delete[] calls in line_descriptor.cpp

another fix in line descriptor module for Win32 MSVC

removed wildcards from fg/bg path in ICFDetector::train

fixed the hamming distance function not to use 64-bit pop count.

fixed the hamming distance function not to use 64-bit pop count. This should fix compile errors on Windows