Class Hierarchy

This inheritance list is sorted roughly, but not completely, alphabetically:

[detail level 12]

CDepthTools::Camera	Represents basic intrinsic parameters used to project pixels into a point cloud
CCCS_OpenCV	Wrapper for running CCS using OpenCV images
CCIS_OpenCV	Wrapper for running CIS with OpenCV images
CConnectedComponents	Efficient (multi-label) connected components algorithm
CCRS_OpenCV	Wrapper for running CRS on OpenCV images
CDASP_OpenCV	Wrapper for running DASP on OpenCV images
CDepthTools	Tools for using depth information
CERGC_OpenCV	Wrapper for running ERGC on OpenCV images
CERS_OpenCV	Wrapper for running ERS on OpenCV images
CETPS_OpenCV	Wrapper for running ETPS on OpenCV images
CEvaluation	Provides measures to evaluate (over-) segmentations
CEvaluationSummary::EvaluationMetrics	Available metrics, see evaluation.h
CEvaluationSummary::EvaluationStatistics	Available statistics that may be computed for each metric
CEvaluationSummary	Given a directory of superpixel segmentations and a directory of ground truth segmentations, this class is used to generate a CSV file of statistics of different metrics
CFH_OpenCV	Wrapper for running FH on OpenCV images
CGraphSegmentation	Implementation of graph based image segmentation as described in the paper by Felzenswalb and Huttenlocher
▼CGraphSegmentationDistance	Interface to be implemented by a concerete distance. The distance defines how the weights between nodes in the image graph are computed. See the paper by Felzenswalb and Huttenlocher for details. Essentially, derived classes only need to overwrite the () operator
CGraphSegmentationEuclideanRGB	Euclidean RGB distance
CGraphSegmentationManhattenRGB	Manhatten (i.e. L1) distance
▼CGraphSegmentationMagic	The magic part of the graph segmentation, i.e. s given two nodes decide whether to add an edge between them (i.e. merge the corresponding segments). See the paper by Felzenswalb and Huttenlocher for details
CGraphSegmentationMagicThreshold
CImageEdge	Represents an edge between two pixels in an image. Each edge is characterized by a weight and the adjacent nodes
CImageEdgeSorter	Class for sorting edges according to weight
CImageGraph	Represents an image graph, consisting of one node per pixel which are 4-connected
CImageNode	Represents a pixel in a video. Each pixel is represented by its color which is needed to compute the weights between pixels
CIOUtil	I/O utilities
CLSC_OpenCV	Wrapper for running LSC on OpenCV images
CMSS_OpenCV	Wrapper for running MSS on OpenCV images
CParameterOptimizationTool	Tool to guide parameter optimization using grid search
CPB_OpenCV	Wrapper for running PB on OpenCV images
CRobustnessTool	Tool evaluating the robustness for different filters/enhancement/transformations
▼CRobustnessToolDriver	Driver for different filters/enhancements/transformations
CBilateralFilterDriver	Bilateral filter driver
CBlurDriver	Blur driver
CGaussianBlurDriver	Gaussian blur filter
CGaussianNoiseDriver	Additive Gaussian noise and Gaussian sampling error driver
CMedianBlurDriver	Median blur driver
CMotionBlurDriver	Motion blur driver
CPoissonNoiseDriver	Poisson noise driver
CRotationDriver	Rotation driver
CSaltAndPepperNoiseDriver	Salt and pepper noise driver
CShearDriver	Vertical and horizontal shear driver
CTranslationDriver	Translation driver
Cscost
CSLIC_OpenCV	Wrapper for running SLIC on OpenCV images
CSuperpixelTools	Superpixel utilities
CEvaluationSummary::SuperpixelVisualizations	Available superpixel visualizations, see visualization.h
CTransformation	Utility class for image and ground truth transofmrations
CVC_OpenCV	Wrapper for running VC on OpenCV images
CVCCS_OpenCV_PCL	Wrapper for running PCL on OpenCV images given the point cloud as OpenCV image
CVisualization	Some basic visualizations of superpixel segmentations
CVLSLIC_OpenCV	Wrapper for running vlSLIC on OpenCV images