added error msg for samples

Minor clean up. There was no need to keep these lines.

optflow: fix test failure

MSVS2013:
- DenseOpticalFlow_GlobalPatchColliderDCT.ReferenceAccuracy
- DenseOpticalFlow_GlobalPatchColliderWHT.ReferenceAccuracy

allows trading corner precision for corner quantity

* Minor fixes

* Start adding correspondence finding

* Added finding of correspondences using GPC

* New evaluation tool for GPC

* Changed default parameters

* Display ground truth in the evaluation tool

* Added training tool for MPI Sintel dataset

* Added the training tool for Middlebury dataset

* Added some OpenCL optimization

* Added explanatory notes

* Minor improvements: time measurements + little ocl optimization

* Added demos

* Fixed warnings

* Make parameter struct assignable

* Fix warning

* Proper command line argument usage

* Prettified training tool, added parameters

* Fixed VS warning

* Fixed VS warning

* Using of compressed forest.yml.gz files by default to save space

* Added OpenCL flag to the evaluation tool

* Updated documentation

* Major speed and memory improvements:
1) Added new (optional) type of patch descriptors which are much faster. Retraining with option --descriptor-type=1 is required.
2) Got rid of hash table for descriptors, less memory usage.

* Fixed various floating point errors related to precision.
SIMD for dot product, forest traversing is a little bit faster now.

* Tolerant floating point comparison

* Triplets

* Added comment

* Choosing negative sample among nearest neighbors

* Fix warning

* Usage of parallel_for_() in critical places. Performance improvments.

* Simulated annealing heuristic

* Moved OpenCL kernel to separate file

* Moved implementation to source file

* Added basic accuracy tests for GPC and PCAFlow

* Fixing warnings

* Test accuracy constraints were too strict

* Test accuracy constraints were too strict

* Make tests more lightweight

It is required for proper work of toolchains

changed double *p to vector<double>

also add shortcut if markers are aligned with image axes

fix for feature2d java wrappers as described in this post: http://answers.opencv.org/question/101675/surfsift-java-wrapper-for-opencv-3xosx-1011/

Fixing compilation

Patched the saliency module to use ObjectivenessBING bounding box
proposals from python.

Usage:

```
bing = cv2.saliency.ObjectnessBING()
img = cv2.imread('/home/ignotus/Pictures/10376146_973700932714682_2056967515849182952_n.jpg')
bing.computeSaliency(img)
```

fixed some compile warnings in dnn & protobuf; improved convolution layer performance when blas is not available by parallelizing gemmCPU() function in dnn

* Fix kcfTracker when called from Python bindings. The variable boundingBox in updateImpl when called from Python is initialized with 0s and it needs to be updated with the tracker state.

* Fix to return the bbox correctly in the first frame in Python