A B C D E F G H I J K L M N O P Q R S T U V W

P

pad(String, String, int, boolean) - Method in class codebook_generation.SimpleKMeansWithOutput

ParisQueries - Static variable in class evaluation.EvaluationFromFile

ParisSize - Static variable in class evaluation.EvaluationFromFile

PCA - Class in dimensionality_reduction

The following is a simple example of how to perform basic principle component analysis in EJML.

PCA(int, int, int) - Constructor for class dimensionality_reduction.PCA

PCALearning - Class in dimensionality_reduction

This class can be used to learn a PCA projection matrix.

PCALearning() - Constructor for class dimensionality_reduction.PCALearning

PCAProjection - Class in dimensionality_reduction

This class can be used to perform PCA projection of a set of vectors using an already learned PCA projection matrix.

PCAProjection() - Constructor for class dimensionality_reduction.PCAProjection

percentage - Variable in class vector_aggregation.VladAggregatorWithFiltering

The percentage of features to be retained.

percentageRetained - Variable in class feature_filtering.RandomFiltering

The percentage of descriptors that will be randomly filtered.

percentages - Static variable in class vector_aggregation.VladAggregatorWithFiltering

Percentages for which thresholds have been pre-calculated for the std and ratio methods.

percentiles - Static variable in class feature_filtering.EntropyBasedFiltering

Percentile values for which thresholds have been pre-calculated.

percentiles - Static variable in class feature_filtering.VarianceBasedFiltering

Percentile values for which thresholds have been pre-calculated.

persistentIndexUpdateTime - Variable in class data_structures.ADC

persistentIndexUpdateTime - Variable in class data_structures.IVFADC

pixelRegion(int, int, Class<T>) - Static method in class utilities.boofcv_extensions.FactoryDescribePointAlgsNormalization

pixelRegionNCC(int, int, Class<T>) - Static method in class utilities.boofcv_extensions.FactoryDescribePointAlgsNormalization

posSet - Variable in class evaluation.EvaluationFromFile

Contains the names of positive images.

power - Static variable in class codebook_generation.CodebookGeneration

The power to use when power-normalization is applied.

power - Static variable in class experimental_data_creation.BestFeatureData

The power in used in power-normalization of the local features.

powerNormalization - Variable in class feature_extraction.DescriptorExtractor

Whether to apply power normalization or not.

pqByteCodes - Variable in class data_structures.ADC

The product-quantization codes for all vector are stored in this list if the code can fit in the byte range.

pqShortCodes - Variable in class data_structures.ADC

The product-quantization codes for all vector are stored in this list if the code cannot fit in the byte range.

preserveInstancesOrderTipText() - Method in class codebook_generation.SimpleKMeansWithOutput

Returns the tip text for this property.

process(double, double, double, double, SurfFeature) - Method in class utilities.boofcv_extensions.DescribePointSiftNormalization

process(double, double, double, double, int, double, SurfFeature) - Method in class utilities.boofcv_extensions.DescribePointSiftNormalization

Compute the descriptor with information on which level in the scale-space to use.

process(ImageFloat32) - Method in class utilities.boofcv_extensions.DetectDescribeSiftNormalization

Processes the image and extracts SIFT features

product_quantization - package product_quantization

productQuantizationTime - Variable in class data_structures.ADC

productQuantizationTime - Variable in class data_structures.IVFADC

productQuantizer - Variable in class data_structures.ADC

The sub-quantizers.

productQuantizer - Variable in class data_structures.IVFADC

The sub-quantizers.

ProductQuantizerLearning - Class in product_quantization

The purpose of this class is to learn the sub-quantizers of a Product Quantizer.

ProductQuantizerLearning() - Constructor for class product_quantization.ProductQuantizerLearning