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Merge pull request #9075 from TonyLianLong:master

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Remove unnecessary Non-ASCII characters from source code (#9075)

* Remove unnecessary Non-ASCII characters from source code

Remove unnecessary Non-ASCII characters and replace them with ASCII
characters

* Remove dashes in the @param statement

Remove dashes and place single space in the @param statement to keep
coding style

* misc: more fixes for non-ASCII symbols

* misc: fix non-ASCII symbol in CMake file
This commit is contained in:
Tony Lian 2017-07-03 09:14:17 -07:00 committed by Alexander Alekhin
parent 9aaf6a66a3
commit c8783f3e23
25 changed files with 75 additions and 75 deletions
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4
3rdparty/carotene/src/colorconvert.cpp vendored
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@ -2466,9 +2466,9 @@ void yuv420sp2rgb(const Size2D &size,
// B = [((149*y)/2 + (-17705+129*u) )/2]/32
// error estimation:
//Rerr = 0.0000625 * y − 0.00225 * v − 0.287
//Rerr = 0.0000625 * y - 0.00225 * v - 0.287
//Gerr = 0.0000625 * y + 0.0005 * v + 0.000375 * u + 0.128625
//Berr = 0.0000625 * y − 0.002375 * u - 0.287375
//Berr = 0.0000625 * y - 0.002375 * u - 0.287375
//real error test:
//=================

2
cmake/OpenCVDetectCStripes.cmake
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@ -1,6 +1,6 @@
if(WIN32)
find_path( CSTRIPES_LIB_DIR
NAMES "С=.lib"
NAMES "C=.lib"
DOC "The path to C= lib and dll")
if(CSTRIPES_LIB_DIR)
ocv_include_directories("${CSTRIPES_LIB_DIR}/..")

4
modules/calib3d/src/fisheye.cpp
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@ -379,9 +379,9 @@ void cv::fisheye::undistortPoints( InputArray distorted, OutputArray undistorted
double theta_d = sqrt(pw[0]*pw[0] + pw[1]*pw[1]);
// the current camera model is only valid up to 180° FOV
// the current camera model is only valid up to 180 FOV
// for larger FOV the loop below does not converge
// clip values so we still get plausible results for super fisheye images > 180°
// clip values so we still get plausible results for super fisheye images > 180 grad
theta_d = min(max(-CV_PI/2., theta_d), CV_PI/2.);
if (theta_d > 1e-8)

2
modules/calib3d/src/homography_decomp.cpp
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@ -16,7 +16,7 @@
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2014, Samson Yilma¸ (samson_yilma@yahoo.com), all rights reserved.
// Copyright (C) 2014, Samson Yilma (samson_yilma@yahoo.com), all rights reserved.
//
// Third party copyrights are property of their respective owners.
//

6
modules/calib3d/src/rho.cpp
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@ -1248,11 +1248,11 @@ inline void RHO_HEST_REFC::rndSmpl(unsigned sampleSize,
/**
* Selection Sampling:
*
* Algorithm S (Selection sampling technique). To select n records at random from a set of N, where 0 < n ≤ N.
* S1. [Initialize.] Set t ← 0, m ← 0. (During this algorithm, m represents the number of records selected so far,
* Algorithm S (Selection sampling technique). To select n records at random from a set of N, where 0 < n <= N.
* S1. [Initialize.] Set t = 0, m = 0. (During this algorithm, m represents the number of records selected so far,
* and t is the total number of input records that we have dealt with.)
* S2. [Generate U.] Generate a random number U, uniformly distributed between zero and one.
* S3. [Test.] If (N – t)U ≥ n – m, go to step S5.
* S3. [Test.] If (N - t)U >= n - m, go to step S5.
* S4. [Select.] Select the next record for the sample, and increase m and t by 1. If m < n, go to step S2;
* otherwise the sample is complete and the algorithm terminates.
* S5. [Skip.] Skip the next record (do not include it in the sample), increase t by 1, and go back to step S2.

2
modules/calib3d/src/triangulate.cpp
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@ -281,7 +281,7 @@ cvCorrectMatches(CvMat *F_, CvMat *points1_, CvMat *points2_, CvMat *new_points1
c = cvGetReal2D(RTFTR,2,1);
d = cvGetReal2D(RTFTR,2,2);
// Form the polynomial g(t) = k6*t⁶ + k5*t⁵ + k4*t⁴ + k3*t³ + k2*t² + k1*t + k0
// Form the polynomial g(t) = k6*t^6 + k5*t^5 + k4*t^4 + k3*t^3 + k2*t^2 + k1*t + k0
// from f1, f2, a, b, c and d
cvSetReal2D(polynomial,0,6,( +b*c*c*f1*f1*f1*f1*a-a*a*d*f1*f1*f1*f1*c ));
cvSetReal2D(polynomial,0,5,( +f2*f2*f2*f2*c*c*c*c+2*a*a*f2*f2*c*c-a*a*d*d*f1*f1*f1*f1+b*b*c*c*f1*f1*f1*f1+a*a*a*a ));

2
modules/calib3d/test/test_homography_decomp.cpp
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@ -13,7 +13,7 @@
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2014, Samson Yilma¸ (samson_yilma@yahoo.com), all rights reserved.
// Copyright (C) 2014, Samson Yilma (samson_yilma@yahoo.com), all rights reserved.
//
// Third party copyrights are property of their respective owners.
//

2
modules/core/include/opencv2/core/persistence.hpp
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@ -474,7 +474,7 @@ template<> CV_EXPORTS void DefaultDeleter<CvFileStorage>::operator ()(CvFileStor
The node is used to store each and every element of the file storage opened for reading. When
XML/YAML file is read, it is first parsed and stored in the memory as a hierarchical collection of
nodes. Each node can be a “leaf” that is contain a single number or a string, or be a collection of
nodes. Each node can be a "leaf" that is contain a single number or a string, or be a collection of
other nodes. There can be named collections (mappings) where each element has a name and it is
accessed by a name, and ordered collections (sequences) where elements do not have names but rather
accessed by index. Type of the file node can be determined using FileNode::type method.

30
modules/core/include/opencv2/core/utility.hpp
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@ -200,13 +200,13 @@ be called outside of parallel region.
OpenCV will try to run it's functions with specified threads number, but some behaviour differs from
framework:
- `TBB` – User-defined parallel constructions will run with the same threads number, if
- `TBB` - User-defined parallel constructions will run with the same threads number, if
another does not specified. If later on user creates own scheduler, OpenCV will use it.
- `OpenMP` – No special defined behaviour.
- `Concurrency` – If threads == 1, OpenCV will disable threading optimizations and run it's
- `OpenMP` - No special defined behaviour.
- `Concurrency` - If threads == 1, OpenCV will disable threading optimizations and run it's
functions sequentially.
- `GCD` – Supports only values \<= 0.
- `C=` – No special defined behaviour.
- `GCD` - Supports only values \<= 0.
- `C=` - No special defined behaviour.
@param nthreads Number of threads used by OpenCV.
@sa getNumThreads, getThreadNum
*/
@ -217,13 +217,13 @@ CV_EXPORTS_W void setNumThreads(int nthreads);
Always returns 1 if OpenCV is built without threading support.
The exact meaning of return value depends on the threading framework used by OpenCV library:
- `TBB` – The number of threads, that OpenCV will try to use for parallel regions. If there is
- `TBB` - The number of threads, that OpenCV will try to use for parallel regions. If there is
any tbb::thread_scheduler_init in user code conflicting with OpenCV, then function returns
default number of threads used by TBB library.
- `OpenMP` – An upper bound on the number of threads that could be used to form a new team.
- `Concurrency` – The number of threads, that OpenCV will try to use for parallel regions.
- `GCD` – Unsupported; returns the GCD thread pool limit (512) for compatibility.
- `C=` – The number of threads, that OpenCV will try to use for parallel regions, if before
- `OpenMP` - An upper bound on the number of threads that could be used to form a new team.
- `Concurrency` - The number of threads, that OpenCV will try to use for parallel regions.
- `GCD` - Unsupported; returns the GCD thread pool limit (512) for compatibility.
- `C=` - The number of threads, that OpenCV will try to use for parallel regions, if before
called setNumThreads with threads \> 0, otherwise returns the number of logical CPUs,
available for the process.
@sa setNumThreads, getThreadNum
@ -234,12 +234,12 @@ CV_EXPORTS_W int getNumThreads();
returns 0 if called outside of parallel region.
The exact meaning of return value depends on the threading framework used by OpenCV library:
- `TBB` – Unsupported with current 4.1 TBB release. Maybe will be supported in future.
- `OpenMP` – The thread number, within the current team, of the calling thread.
- `Concurrency` – An ID for the virtual processor that the current context is executing on (0
- `TBB` - Unsupported with current 4.1 TBB release. Maybe will be supported in future.
- `OpenMP` - The thread number, within the current team, of the calling thread.
- `Concurrency` - An ID for the virtual processor that the current context is executing on (0
for master thread and unique number for others, but not necessary 1,2,3,...).
- `GCD` – System calling thread's ID. Never returns 0 inside parallel region.
- `C=` – The index of the current parallel task.
- `GCD` - System calling thread's ID. Never returns 0 inside parallel region.
- `C=` - The index of the current parallel task.
@sa setNumThreads, getNumThreads
*/
CV_EXPORTS_W int getThreadNum();

2
modules/cudaobjdetect/src/hog.cpp
View File

@ -251,7 +251,7 @@ namespace
// Navneet Dalal and Bill Triggs. Histograms of oriented gradients for
// human detection. In International Conference on Computer Vision and
// Pattern Recognition, volume 2, pages 886–893, June 2005
// Pattern Recognition, volume 2, pages 886-893, June 2005
// http://lear.inrialpes.fr/people/triggs/pubs/Dalal-cvpr05.pdf (28.07.2015) [Figure 5]
CV_Assert(block_stride == (block_size / 2));

2
modules/cudaoptflow/include/opencv2/cudaoptflow.hpp
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@ -210,7 +210,7 @@ public:
// FarnebackOpticalFlow
//
/** @brief Class computing a dense optical flow using the Gunnar Farneback’s algorithm.
/** @brief Class computing a dense optical flow using the Gunnar Farneback's algorithm.
*/
class CV_EXPORTS FarnebackOpticalFlow : public DenseOpticalFlow
{

2
modules/features2d/src/brisk.cpp
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@ -745,7 +745,7 @@ BRISK_Impl::computeDescriptorsAndOrOrientation(InputArray _image, InputArray _ma
int theta;
if (kp.angle==-1)
{
// don't compute the gradient direction, just assign a rotation of 0°
// don't compute the gradient direction, just assign a rotation of 0
theta = 0;
}
else

2
modules/features2d/src/mser.cpp
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@ -25,7 +25,7 @@
* TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT
* OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY
* OF SUCH DAMAGE.
* Copyright© 2009, Liu Liu All rights reserved.
* Copyright (C) 2009, Liu Liu All rights reserved.
*
* OpenCV functions for MSER extraction
*

2
modules/flann/include/opencv2/flann/dist.h
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@ -698,7 +698,7 @@ struct KL_Divergence
typedef typename Accumulator<T>::Type ResultType;
/**
* Compute the Kullback–Leibler divergence
* Compute the Kullback-Leibler divergence
*/
template <typename Iterator1, typename Iterator2>
ResultType operator()(Iterator1 a, Iterator2 b, size_t size, ResultType worst_dist = -1) const

6
modules/highgui/src/window_carbon.cpp
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@ -282,7 +282,7 @@ static void icvPutImage( CvWindow* window )
static void icvUpdateWindowSize( const CvWindow* window )
{
int width = 0, height = 240; /* init à al taille de base de l'image*/
int width = 0, height = 240;
Rect globalBounds;
GetWindowBounds(window->window, kWindowContentRgn, &globalBounds);
@ -1031,7 +1031,7 @@ static pascal OSStatus windowEventHandler(EventHandlerCallRef nextHandler, Event
GetWindowBounds(theWindow, kWindowStructureRgn, &structure);
GetWindowBounds(theWindow, kWindowContentRgn, &content);
lx = (int)point.x - content.left + structure.left;
ly = (int)point.y - window->trackbarheight - content.top + structure.top; /* minus la taille des trackbars */
ly = (int)point.y - window->trackbarheight - content.top + structure.top;
if (window->flags & CV_WINDOW_AUTOSIZE) {//FD
//printf("was %d,%d\n", lx, ly);
/* scale the mouse coordinates */
@ -1039,7 +1039,7 @@ static pascal OSStatus windowEventHandler(EventHandlerCallRef nextHandler, Event
ly = ly * window->imageHeight / (content.bottom - content.top - window->trackbarheight);
}
if (lx>0 && ly >0){ /* a remettre dans les coordonnées locale */
if (lx>0 && ly >0){
window->on_mouse (event, lx, ly, flags, window->on_mouse_param);
return noErr;
}

58
modules/imgproc/include/opencv2/imgproc.hpp
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@ -198,8 +198,8 @@ int main(int argc, const char *argv[])
The Subdiv2D class described in this section is used to perform various planar subdivision on
a set of 2D points (represented as vector of Point2f). OpenCV subdivides a plane into triangles
using the Delaunay’s algorithm, which corresponds to the dual graph of the Voronoi diagram.
In the figure below, the Delaunay’s triangulation is marked with black lines and the Voronoi
using the Delaunay's algorithm, which corresponds to the dual graph of the Voronoi diagram.
In the figure below, the Delaunay's triangulation is marked with black lines and the Voronoi
diagram with red lines.
![Delaunay triangulation (black) and Voronoi (red)](pics/delaunay_voronoi.png)
@ -955,7 +955,7 @@ public:
/** @overload
@param rect – Rectangle that includes all of the 2D points that are to be added to the subdivision.
@param rect Rectangle that includes all of the 2D points that are to be added to the subdivision.
The function creates an empty Delaunay subdivision where 2D points can be added using the function
insert() . All of the points to be added must be within the specified rectangle, otherwise a runtime
@ -965,14 +965,14 @@ public:
/** @brief Creates a new empty Delaunay subdivision
@param rect – Rectangle that includes all of the 2D points that are to be added to the subdivision.
@param rect Rectangle that includes all of the 2D points that are to be added to the subdivision.
*/
CV_WRAP void initDelaunay(Rect rect);
/** @brief Insert a single point into a Delaunay triangulation.
@param pt – Point to insert.
@param pt Point to insert.
The function inserts a single point into a subdivision and modifies the subdivision topology
appropriately. If a point with the same coordinates exists already, no new point is added.
@ -984,7 +984,7 @@ public:
/** @brief Insert multiple points into a Delaunay triangulation.
@param ptvec – Points to insert.
@param ptvec Points to insert.
The function inserts a vector of points into a subdivision and modifies the subdivision topology
appropriately.
@ -993,9 +993,9 @@ public:
/** @brief Returns the location of a point within a Delaunay triangulation.
@param pt – Point to locate.
@param edge – Output edge that the point belongs to or is located to the right of it.
@param vertex – Optional output vertex the input point coincides with.
@param pt Point to locate.
@param edge Output edge that the point belongs to or is located to the right of it.
@param vertex Optional output vertex the input point coincides with.
The function locates the input point within the subdivision and gives one of the triangle edges
or vertices.
@ -1008,15 +1008,15 @@ public:
vertex will contain a pointer to the vertex.
- The point is outside the subdivision reference rectangle. The function returns PTLOC_OUTSIDE_RECT
and no pointers are filled.
- One of input arguments is invalid. A runtime error is raised or, if silent or “parent” error
- One of input arguments is invalid. A runtime error is raised or, if silent or "parent" error
processing mode is selected, CV_PTLOC_ERROR is returned.
*/
CV_WRAP int locate(Point2f pt, CV_OUT int& edge, CV_OUT int& vertex);
/** @brief Finds the subdivision vertex closest to the given point.
@param pt – Input point.
@param nearestPt – Output subdivision vertex point.
@param pt Input point.
@param nearestPt Output subdivision vertex point.
The function is another function that locates the input point within the subdivision. It finds the
subdivision vertex that is the closest to the input point. It is not necessarily one of vertices
@ -1029,7 +1029,7 @@ public:
/** @brief Returns a list of all edges.
@param edgeList – Output vector.
@param edgeList Output vector.
The function gives each edge as a 4 numbers vector, where each two are one of the edge
vertices. i.e. org_x = v[0], org_y = v[1], dst_x = v[2], dst_y = v[3].
@ -1038,7 +1038,7 @@ public:
/** @brief Returns a list of the leading edge ID connected to each triangle.
@param leadingEdgeList – Output vector.
@param leadingEdgeList Output vector.
The function gives one edge ID for each triangle.
*/
@ -1046,7 +1046,7 @@ public:
/** @brief Returns a list of all triangles.
@param triangleList – Output vector.
@param triangleList Output vector.
The function gives each triangle as a 6 numbers vector, where each two are one of the triangle
vertices. i.e. p1_x = v[0], p1_y = v[1], p2_x = v[2], p2_y = v[3], p3_x = v[4], p3_y = v[5].
@ -1055,9 +1055,9 @@ public:
/** @brief Returns a list of all Voroni facets.
@param idx – Vector of vertices IDs to consider. For all vertices you can pass empty vector.
@param facetList – Output vector of the Voroni facets.
@param facetCenters – Output vector of the Voroni facets center points.
@param idx Vector of vertices IDs to consider. For all vertices you can pass empty vector.
@param facetList Output vector of the Voroni facets.
@param facetCenters Output vector of the Voroni facets center points.
*/
CV_WRAP void getVoronoiFacetList(const std::vector<int>& idx, CV_OUT std::vector<std::vector<Point2f> >& facetList,
@ -1065,8 +1065,8 @@ public:
/** @brief Returns vertex location from vertex ID.
@param vertex – vertex ID.
@param firstEdge – Optional. The first edge ID which is connected to the vertex.
@param vertex vertex ID.
@param firstEdge Optional. The first edge ID which is connected to the vertex.
@returns vertex (x,y)
*/
@ -1074,8 +1074,8 @@ public:
/** @brief Returns one of the edges related to the given edge.
@param edge – Subdivision edge ID.
@param nextEdgeType - Parameter specifying which of the related edges to return.
@param edge Subdivision edge ID.
@param nextEdgeType Parameter specifying which of the related edges to return.
The following values are possible:
- NEXT_AROUND_ORG next around the edge origin ( eOnext on the picture below if e is the input edge)
- NEXT_AROUND_DST next around the edge vertex ( eDnext )
@ -1094,7 +1094,7 @@ public:
/** @brief Returns next edge around the edge origin.
@param edge – Subdivision edge ID.
@param edge Subdivision edge ID.
@returns an integer which is next edge ID around the edge origin: eOnext on the
picture above if e is the input edge).
@ -1103,8 +1103,8 @@ public:
/** @brief Returns another edge of the same quad-edge.
@param edge – Subdivision edge ID.
@param rotate - Parameter specifying which of the edges of the same quad-edge as the input
@param edge Subdivision edge ID.
@param rotate Parameter specifying which of the edges of the same quad-edge as the input
one to return. The following values are possible:
- 0 - the input edge ( e on the picture below if e is the input edge)
- 1 - the rotated edge ( eRot )
@ -1118,8 +1118,8 @@ public:
/** @brief Returns the edge origin.
@param edge – Subdivision edge ID.
@param orgpt – Output vertex location.
@param edge Subdivision edge ID.
@param orgpt Output vertex location.
@returns vertex ID.
*/
@ -1127,8 +1127,8 @@ public:
/** @brief Returns the edge destination.
@param edge – Subdivision edge ID.
@param dstpt – Output vertex location.
@param edge Subdivision edge ID.
@param dstpt Output vertex location.
@returns vertex ID.
*/

2
modules/imgproc/src/connectedcomponents.cpp
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@ -2586,7 +2586,7 @@ namespace cv{
}
};//End struct LabelingGranaParallel
// Based on <EFBFBD>Optimized Block-based Connected Components Labeling with Decision Trees<65>, Costantino Grana et al
// Based on "Optimized Block-based Connected Components Labeling with Decision Trees", Costantino Grana et al
// Only for 8-connectivity
template<typename LabelT, typename PixelT, typename StatsOp = NoOp >
struct LabelingGrana{

2
modules/imgproc/src/grabcut.cpp
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@ -47,7 +47,7 @@ using namespace cv;
/*
This is implementation of image segmentation algorithm GrabCut described in
"GrabCut — Interactive Foreground Extraction using Iterated Graph Cuts".
"GrabCut - Interactive Foreground Extraction using Iterated Graph Cuts".
Carsten Rother, Vladimir Kolmogorov, Andrew Blake.
*/

2
modules/photo/src/calibrate.cpp
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@ -120,7 +120,7 @@ public:
LDR_SIZE + (int)points.size(), CV_32F);
Mat B = Mat::zeros(A.rows, 1, CV_32F);
// include the data−fitting equations
// include the data-fitting equations
int k = 0;
for(size_t i = 0; i < points.size(); i++) {
for(size_t j = 0; j < images.size(); j++) {

2
modules/stitching/include/opencv2/stitching/detail/motion_estimators.hpp
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@ -201,7 +201,7 @@ protected:
// Threshold to filter out poorly matched image pairs
double conf_thresh_;
//Levenberg–Marquardt algorithm termination criteria
//Levenberg-Marquardt algorithm termination criteria
TermCriteria term_criteria_;
// Camera parameters matrix (CV_64F)

2
modules/stitching/include/opencv2/stitching/detail/warpers.hpp
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@ -243,7 +243,7 @@ struct CV_EXPORTS SphericalProjector : ProjectorBase
/** @brief Warper that maps an image onto the unit sphere located at the origin.
Projects image onto unit sphere with origin at (0, 0, 0) and radius scale, measured in pixels.
A 360° panorama would therefore have a resulting width of 2 * scale * PI pixels.
A 360 panorama would therefore have a resulting width of 2 * scale * PI pixels.
Poles are located at (0, -1, 0) and (0, 1, 0) points.
*/
class CV_EXPORTS SphericalWarper : public RotationWarperBase<SphericalProjector>

2
modules/ts/include/opencv2/ts/ts_gtest.h
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@ -8015,7 +8015,7 @@ namespace edit_distance {
// Returns the optimal edits to go from 'left' to 'right'.
// All edits cost the same, with replace having lower priority than
// add/remove.
// Simple implementation of the Wagner–Fischer algorithm.
// Simple implementation of the Wagner-Fischer algorithm.
// See http://en.wikipedia.org/wiki/Wagner-Fischer_algorithm
enum EditType { kMatch, kAdd, kRemove, kReplace };
GTEST_API_ std::vector<EditType> CalculateOptimalEdits(

2
modules/video/include/opencv2/video/tracking.hpp
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@ -544,7 +544,7 @@ public:
*/
CV_EXPORTS_W Ptr<DualTVL1OpticalFlow> createOptFlow_DualTVL1();
/** @brief Class computing a dense optical flow using the Gunnar Farneback’s algorithm.
/** @brief Class computing a dense optical flow using the Gunnar Farneback's algorithm.
*/
class CV_EXPORTS_W FarnebackOpticalFlow : public DenseOpticalFlow
{

6
samples/cpp/tutorial_code/calib3d/real_time_pose_estimation/src/PnPProblem.cpp
View File

@ -20,7 +20,7 @@ cv::Point3f SUB(cv::Point3f v1, cv::Point3f v2);
cv::Point3f get_nearest_3D_point(std::vector<cv::Point3f> &points_list, cv::Point3f origin);
/* Functions for Möller–Trumbore intersection algorithm */
/* Functions for Möller-Trumbore intersection algorithm */
cv::Point3f CROSS(cv::Point3f v1, cv::Point3f v2)
{
@ -45,7 +45,7 @@ cv::Point3f SUB(cv::Point3f v1, cv::Point3f v2)
return tmp_p;
}
/* End functions for Möller–Trumbore intersection algorithm
/* End functions for Möller-Trumbore intersection algorithm
* */
// Function to get the nearest 3D point to the Ray origin
@ -258,7 +258,7 @@ bool PnPProblem::backproject2DPoint(const Mesh *mesh, const cv::Point2f &point2d
}
}
// Möller–Trumbore intersection algorithm
// Möller-Trumbore intersection algorithm
bool PnPProblem::intersect_MollerTrumbore(Ray &Ray, Triangle &Triangle, double *out)
{
const double EPSILON = 0.000001;

2
samples/cpp/tutorial_code/calib3d/real_time_pose_estimation/src/PnPProblem.h
View File

@ -50,7 +50,7 @@ private:
cv::Mat _P_matrix;
};
// Functions for Möller–Trumbore intersection algorithm
// Functions for Möller-Trumbore intersection algorithm
cv::Point3f CROSS(cv::Point3f v1, cv::Point3f v2);
double DOT(cv::Point3f v1, cv::Point3f v2);
cv::Point3f SUB(cv::Point3f v1, cv::Point3f v2);