Merge pull request #23900 from kai-waang:fixing-typo

Fixing typos in usac #23900

Just read and correct some typos in `usac`
### Pull Request Readiness Checklist

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- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [ ] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [ ] The feature is well documented and sample code can be built with the project CMake

modules/calib3d/src/usac/degeneracy.cpp

@@ -112,7 +112,7 @@ public:
             return false;
 
         // Checks if points are not collinear
-        // If area of triangle constructed with 3 points is less then threshold then points are collinear:
+        // If area of triangle constructed with 3 points is less than threshold then points are collinear:
         //           |x1 y1 1|             |x1      y1      1|
         // (1/2) det |x2 y2 1| = (1/2) det |x2-x1   y2-y1   0| = det |x2-x1   y2-y1| < 2 * threshold
         //           |x3 y3 1|             |x3-x1   y3-y1   0|       |x3-x1   y3-y1|

modules/calib3d/src/usac/essential_solver.cpp

@@ -142,7 +142,7 @@ public:
             }
 
             std::vector<double> c(11), rs;
-            // filling coefficients of 10-degree polynomial satysfying zero-determinant constraint of essential matrix, ie., det(E) = 0
+            // filling coefficients of 10-degree polynomial satisfying zero-determinant constraint of essential matrix, ie., det(E) = 0
             // based on "An Efficient Solution to the Five-Point Relative Pose Problem" (David Nister)
             // same as in five-point.cpp
             c[10] = (b[0]*b[17]*b[34]+b[26]*b[4]*b[21]-b[26]*b[17]*b[8]-b[13]*b[4]*b[34]-b[0]*b[21]*b[30]+b[13]*b[30]*b[8]);

modules/calib3d/src/usac/fundamental_solver.cpp

@@ -438,7 +438,7 @@ public:
     explicit CovarianceEpipolarSolverImpl (const Mat &points_, bool is_fundamental_) {
         points_size = points_.rows;
         is_fundamental = is_fundamental_;
-        if (is_fundamental) { // normalize image points only for fundmantal matrix
+        if (is_fundamental) { // normalize image points only for fundamental matrix
             std::vector<int> sample(points_size);
             for (int i = 0; i < points_size; i++) sample[i] = i;
             const Ptr<NormTransform> normTr = NormTransform::create(points_);
@@ -558,7 +558,7 @@ public:
         const auto * const pts_ = (float *) calib_points.data;
         // a few point are enough to test
         // actually due to Sampson error minimization, the input R,t do not really matter
-        // for a correct pair there is a sligthly faster convergence
+        // for a correct pair there is a slightly faster convergence
         for (int i = 0; i < 3; i++) { // could be 1 point
             const int rand_inl = 4 * sample[rng.uniform(0, sample_size)];
             Vec3d p1 (pts_[rand_inl], pts_[rand_inl+1], 1), p2(pts_[rand_inl+2], pts_[rand_inl+3], 1);

modules/calib3d/src/usac/pnp_solver.cpp

@@ -196,7 +196,7 @@ public:
                 a2[10] = v * Z;
                 a2[11] = v;
 
-                // fill covarinace matrix
+                // fill covariance matrix
                 for (int j = 0; j < 12; j++)
                     for (int z = j; z < 12; z++)
                         AtA[j * 12 + z] += a1[j] * a1[z] + a2[j] * a2[z];
@@ -227,7 +227,7 @@ public:
                 a2[10] = v * weight_Z;
                 a2[11] = v * weight;
 
-                // fill covarinace matrix
+                // fill covariance matrix
                 for (int j = 0; j < 12; j++)
                     for (int z = j; z < 12; z++)
                         AtA[j * 12 + z] += a1[j] * a1[z] + a2[j] * a2[z];

modules/calib3d/src/usac/ransac_solvers.cpp

@@ -294,7 +294,7 @@ public:
                     params->getUpperIncompleteOfSigmaQuantile()); break;
             case ScoreMethod::SCORE_METHOD_LMEDS :
                 quality = LMedsQuality::create(points_size, threshold, error); break;
-            default: CV_Error(cv::Error::StsNotImplemented, "Score is not imeplemeted!");
+            default: CV_Error(cv::Error::StsNotImplemented, "Score is not implemented!");
         }
 
         const auto is_ge_solver = params->getRansacSolver() == GEM_SOLVER;

modules/calib3d/src/usac/sampler.cpp

@@ -62,8 +62,8 @@ Ptr<UniformSampler> UniformSampler::create(int state, int sample_size_, int poin
 /////////////////////////////////// PROSAC (SIMPLE) SAMPLER ///////////////////////////////////////
 /*
 * PROSAC (simple) sampler does not use array of precalculated T_n (n is subset size) samples, but computes T_n for
-* specific n directy in generateSample() function.
+* specific n directly in generateSample() function.
-* Also, the stopping length (or maximum subset size n*) by default is set to points_size (N) and does not updating
+* Also, the stopping length (or maximum subset size n*) by default is set to points_size (N) and does not update
 * during computation.
 */
 class ProsacSimpleSamplerImpl : public ProsacSimpleSampler {
@@ -176,7 +176,7 @@ protected:
     // In our experiments, the parameter was set to T_N = 200000
     int growth_max_samples;
 
-    // how many time PROSAC generateSample() was called
+    // how many times PROSAC generateSample() was called
     int kth_sample_number;
     Ptr<UniformRandomGenerator> random_gen;
 public:
@@ -488,7 +488,7 @@ public:
 
         points_large_neighborhood_size = 0;
 
-        // find indicies of points that have sufficient neighborhood (at least sample_size-1)
+        // find indices of points that have sufficient neighborhood (at least sample_size-1)
         for (int pt_idx = 0; pt_idx < points_size; pt_idx++)
             if ((int)neighborhood_graph->getNeighbors(pt_idx).size() >= sample_size-1)
                 points_large_neighborhood[points_large_neighborhood_size++] = pt_idx;

modules/calib3d/src/usac/termination.cpp

@@ -19,7 +19,7 @@ public:
 
     /*
      * Get upper bound iterations for any sample number
-     * n is points size, w is inlier ratio, p is desired probability, k is expceted number of iterations.
+     * n is points size, w is inlier ratio, p is desired probability, k is expected number of iterations.
      * 1 - p = (1 - w^n)^k,
      * k = log_(1-w^n) (1-p)
      * k = ln (1-p) / ln (1-w^n)

modules/calib3d/src/usac/utils.cpp

@@ -344,10 +344,10 @@ void Utils::decomposeProjection (const Mat &P, Matx33d &K, Matx33d &R, Vec3d &t,
 }
 
 double Utils::getPoissonCDF (double lambda, int inliers) {
-    double exp_lamda = exp(-lambda), cdf = exp_lamda, lambda_i_div_fact_i = 1;
+    double exp_lambda = exp(-lambda), cdf = exp_lambda, lambda_i_div_fact_i = 1;
     for (int i = 1; i <= inliers; i++) {
         lambda_i_div_fact_i *= (lambda / i);
-        cdf += exp_lamda * lambda_i_div_fact_i;
+        cdf += exp_lambda * lambda_i_div_fact_i;
         if (fabs(cdf - 1) < DBL_EPSILON) // cdf is almost 1
             break;
     }