| /external/opencv3/modules/core/src/ |
| D | pca.cpp | 53 PCA::PCA() {} in PCA() function in cv::PCA
55 PCA::PCA(InputArray data, InputArray _mean, int flags, int maxComponents) in PCA() function in cv::PCA
60 PCA::PCA(InputArray data, InputArray _mean, int flags, double retainedVariance) in PCA() function in cv::PCA
65 PCA& PCA::operator()(InputArray _data, InputArray __mean, int flags, int maxComponents) in operator ()()
151 void PCA::write(FileStorage& fs ) const in write()
161 void PCA::read(const FileNode& fs) in read()
202 PCA& PCA::operator()(InputArray _data, InputArray __mean, int flags, double retainedVariance) in operator ()()
292 void PCA::project(InputArray _data, OutputArray result) const in project()
315 Mat PCA::project(InputArray data) const in project()
322 void PCA::backProject(InputArray _data, OutputArray result) const in backProject()
[all …]
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| D | matmul.cpp | 3392 cv::PCA pca; in cvCalcPCA()
3439 cv::PCA pca; in cvProjectPCA()
3470 cv::PCA pca; in cvBackProjectPCA()
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| /external/opencv3/samples/cpp/ |
| D | pca.cpp | 95 PCA pca;
108 p->pca = PCA(p->data, cv::Mat(), PCA::DATA_AS_ROW, var); in onTrackbar()
153 …PCA pca(data, cv::Mat(), PCA::DATA_AS_ROW, 0.95); // trackbar is initially set here, also this is … in main()
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| /external/opencv3/doc/tutorials/ml/introduction_to_pca/ |
| D | introduction_to_pca.markdown | 1 Introduction to Principal Component Analysis (PCA) {#tutorial_introduction_to_pca}
9 - Use the OpenCV class @ref cv::PCA to calculate the orientation of an object.
11 What is PCA?
14 Principal Component Analysis (PCA) is a statistical procedure that extracts the most important feat…
18 …tern (indicated by the blue line) which is hard to dismiss. A key point of PCA is the Dimensionali…
22 Hence, PCA allows us to find the direction along which our data varies the most. In fact, the resul…
26 … of the eigenvectors is the center of all points in the data set. Applying PCA to N-dimensional da…
98 @note Another example using PCA for dimensionality reduction while maintaining an amount of varianc…
115 …Orientation is extracted by the call of getOrientation() function, which performs all the PCA proc…
118 … 2, where n is the number of data points we have. Then we can perform that PCA analysis. The calcu…
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| /external/opencv3/modules/core/include/opencv2/ |
| D | core.hpp | 2234 class CV_EXPORTS PCA class
2247 PCA();
2258 PCA(InputArray data, InputArray mean, int flags, int maxComponents = 0);
2270 PCA(InputArray data, InputArray mean, int flags, double retainedVariance);
2292 PCA& operator()(InputArray data, InputArray mean, int flags, int maxComponents = 0);
2305 PCA& operator()(InputArray data, InputArray mean, int flags, double retainedVariance);
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| /external/opencv3/doc/tutorials/ml/ |
| D | table_of_content_ml.markdown | 30 Learn what a Principal Component Analysis (PCA) is.
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| /external/clang/lib/Analysis/ |
| D | AnalysisDeclContext.cpp | 287 if (!PCA) in getPseudoConstantAnalysis()
288 PCA.reset(new PseudoConstantAnalysis(getBody())); in getPseudoConstantAnalysis()
289 return PCA.get(); in getPseudoConstantAnalysis()
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| /external/opencv3/samples/cpp/tutorial_code/ml/introduction_to_pca/ |
| D | introduction_to_pca.cpp | 62 PCA pca_analysis(data_pts, Mat(), CV_PCA_DATA_AS_ROW); in getOrientation()
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| /external/opencv3/doc/py_tutorials/py_feature2d/py_brief/ |
| D | py_brief.markdown | 20 methods like PCA, LDA etc. Even other methods like hashing using LSH (Locality Sensitive Hashing) is
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| /external/clang/include/clang/Analysis/ |
| D | AnalysisContext.h | 81 std::unique_ptr<PseudoConstantAnalysis> PCA; variable
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| /external/opencv3/modules/core/test/ |
| D | test_mat.cpp | 309 PCA rPCA( rPoints, Mat(), CV_PCA_DATA_AS_ROW, maxComponents ), cPCA; in run()
518 PCA lPCA; in run()
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| /external/opencv3/modules/ml/doc/ |
| D | ml_intro.markdown | 415 using cv::PCA or similar technique, and train a smaller network on only essential features.
|