added python wrapper macros in edge_filter.hpp

adas fix

- 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

warning fixes

buffer overrun fix

Adaptive manifold filter changes: Memory consuming was reduced and performance was improved (10% average).

Adaptive manifold filter: downsample/upsample operations where paralleled.

adding more clear documentation

updated or_sun dataset loader

added fr_adience dataset loader

added tr_svt benchmark

logtopolar

Fixed some existing doxygen comments

updated or_imagenet dataset loader

Compilation and tests fixes;

fixing tests;

some fixes;

fixing build;

fix warnings;

fix warnings;

added first version of hpe_humaneva dataset loader

updated documentation

minor changes

some changes;

Adjusted test cases for SURF_CUDA, using new APIs

reworking interface;

small fix;