Searched refs:outliers (Results 1 – 12 of 12) sorted by relevance
| /external/opencv3/samples/python2/ |
| D | fitline.py | 60 outliers = np.random.rand(outn, 2) * (w, h)
61 points = np.vstack([line_points, outliers])
64 for p in outliers:
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| /external/opencv3/modules/cudalegacy/test/ |
| D | test_labeling.cpp | 137 int outliers = 0; in checkCorrectness() local
143 outliers++; in checkCorrectness()
146 ASSERT_TRUE(outliers < gpu.cols + gpu.rows); in checkCorrectness()
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| /external/opencv3/modules/calib3d/test/ |
| D | test_affine3d_estimator.cpp | 107 vector<uchar> outliers; in test4Points() local
108 estimateAffine3D(fpts, tpts, aff_est, outliers); in test4Points()
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| /external/opencv3/modules/ts/src/ |
| D | ts_perf.cpp | 640 outliers = 0; in clear()
1297 metrics.outliers = 0; in calcMetrics()
1340 while(*start < minout) ++start, ++metrics.outliers; in calcMetrics()
1341 do --end, ++metrics.outliers; while(*end > maxout); in calcMetrics()
1342 ++end, --metrics.outliers; in calcMetrics()
1347 metrics.outliers = static_cast<int>(times.size() * param_max_outliers / 100); in calcMetrics()
1348 for (unsigned int i = 0; i < metrics.outliers; i++) in calcMetrics()
1415 … EXPECT_LE(m.outliers, std::max((unsigned int)cvCeil(m.samples * param_max_outliers / 100.), 1u)) in validateMetrics()
1449 RecordProperty("outliers", (int)m.outliers); in reportMetrics()
1542 LOGD("outliers =%11u", m.outliers); in reportMetrics()
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| /external/ceres-solver/docs/source/ |
| D | features.rst | 31 involve data. If there is data, there will be outliers. Ceres
33 functions to reduce the influence of outliers.
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| D | tutorial.rst | 45 a scalar function that is used to reduce the influence of outliers on
554 Now suppose the data we are given has some outliers, i.e., we have
564 To deal with outliers, a standard technique is to use a
567 outliers. To associate a loss function in a residual block, we change
589 Using :class:`LossFunction` to reduce the effect of outliers on a
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| D | modeling.rst | 43 outliers on the solution of non-linear least squares problems.
817 input terms that contain outliers, that is, completely bogus
958 performing estimation from data which has substantial outliers,
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| /external/opencv3/doc/py_tutorials/py_feature2d/py_feature_homography/ |
| D | py_feature_homography.markdown | 26 good matches which provide correct estimation are called inliers and remaining are called outliers.
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| /external/opencv3/doc/py_tutorials/py_calib3d/py_epipolar_geometry/ |
| D | py_epipolar_geometry.markdown | 172 2. Fundamental Matrix estimation is sensitive to quality of matches, outliers etc. It becomes worse
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| /external/opencv3/modules/ts/include/opencv2/ts/ |
| D | ts_perf.hpp | 229 unsigned int outliers; member
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| /external/opencv3/doc/tutorials/calib3d/real_time_pose/ |
| D | real_time_pose.markdown | 381 as not, there are false correspondences or also called *outliers*. The [Random Sample
384 … aproximate result as the number of iterations increase. After appyling *Ransac* all the *outliers*
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| /external/v8/test/mozilla/ |
| D | mozilla.status | 226 # cannot handle outliers. See bug #925864.
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