| dlr::computerVision::CameraIntrinsics | This abstract base class defines an interface for classes that describe camera projection and distortion parameters |
| dlr::computerVision::CameraIntrinsicsPinhole | This class represents calibration parameters for a simple pinhole camera model, as described in [1] |
| dlr::computerVision::CameraIntrinsicsPlumbBob | This class represents calibration parameters for cameras conforming to Brown-Conrady "plumb bob" camera model, as described in [1] |
| dlr::computerVision::privateCode::DisjointSet< Type > | This class implements one tree in the "forest of disjoint sets" data structure first described by Bernard Galler and Michael Fischer[1] |
| dlr::computerVision::ExtendedKalmanFilter | This class template implements the ExtendedKalman Filter[??] |
| dlr::computerVision::Image< FORMAT > | This class template represents a 2D image |
| dlr::computerVision::ImageFormatTraits< ImageFormat > | The ImageFormatTraits class template specifies the characteristics of the available image formats |
| dlr::computerVision::KDComparator< Dimension, Type > | This class template is used by the KDTree class template to interact with the data points to be stored in the KD-Tree |
| dlr::computerVision::KDTree< Dimension, Type > | This class implements a basic KD-Tree data structure |
| dlr::computerVision::Kernel< ELEMENT_TYPE > | This class template represents a 2D convolution kernel |
| dlr::computerVision::NChooseKSampleSelector< Sample > | This class template provides capabilities to exhaustively select sequences of samples from a pool of candidates |
| dlr::computerVision::OpticalFlow< Format > | This class uses the method of Lucas and Kanade[1] to estimate the optical flow between two images |
| dlr::computerVision::privateCode::PlumbBobObjective | This functor is called by CameraIntrinsicsPlumbBob::reverseProject() during iterative approximation of reverse projection |
| dlr::computerVision::QuadMap< Type > | This class implements a QuadMap data structure that tessellates 2D space into square regions, and stores an approximately uniform distribution of 2D points in such a way that finding points within the space has complexity approximately logarithmic in the number of points |
| dlr::computerVision::QuadMapComparator< Type > | This class template is used by the QuadMap class template to interact with the data points to be stored in the map |
| dlr::computerVision::RandomSampleSelector< Sample > | This class template provides capabilities to randomly select sequences of samples from a pool of candidates |
| dlr::computerVision::Ransac< Problem > | This class template implements the RANSAC algorithm[1] |
| dlr::computerVision::RansacProblem< Sample, Model > | This class template implements the "Problem" interface required by the Ransac class, above |
| dlr::computerVision::SegmenterFelzenszwalb< EdgeFunctor > | This class implements the image segmentation algorithm described [1] |
1.5.8