New mode is approximately 2-3 times faster than MODE_SGBM
with minimal degradation in quality and uses universal
HAL intrinsics. A performance test was added. The accuracy
test was updated to support the new mode.
It took me a while to figure out what was meant with
OpenCV Error: Assertion failed (i < 0) in getMat
While searching for this error message I found [a list of error
messages](https://adventuresandwhathaveyou.wordpress.com/2014/03/14/opencv-error-messages-suck/)
which also explained what the problem was: The data type for `rvecs` was
not a simple `cv::Mat` but a `std::vector<cv::Mat>`.
After I fixed that, I got the next error message:
OpenCV Error: Assertion failed (ni > 0 && ni == ni1) in
collectCalibrationData, file
/build/buildd/opencv-2.4.9+dfsg/modules/calib3d/src/calibration.cpp,
line 3193
The problem here was that my data type for the `objectPoints` was just
`vector<Vec3f>` and not `vector<vector<Vec3f>>`.
In order to save other people the time looking for this, I added
explicit examples of the needed data types into the documentation of the
function. I had to re-read the current version a couple of times until I
can read the needed levels of `vector<>`. Having this example would have
really helped me there.
Implements the RHO algorithm as presented in
Paper: Bilaniuk, Olexa, Hamid Bazargani, and Robert Laganiere. "Fast
Target Recognition on Mobile Devices: Revisiting Gaussian Elimination
for the Estimation of Planar Homographies." In Computer Vision and
Pattern Recognition Workshops (CVPRW), 2014 IEEE Conference on, pp.
119-125. IEEE, 2014.
- Complete, heavily documented reference C implementation, as well as
temporarily disabled dirty SSE2 port.
- Enabled tests for RHO in test_homography; Currently these fail
presumably due to too-stringent accuracy requirements.
- Refinement and final refinement are not yet functional; Do not pass
their corresponding flags to RHO.