a | |
Abstract | Abstract class to render this object |
kjb::Abstract_dynamics | |
kjb::Likelihood_dynamics | |
kjb::Discrete_change_size | |
kjb::Focal_scale_dynamics | |
kjb::Parapiped_camera_dynamics | |
kjb::Parapiped_stretch_dynamics | |
Abstract_gibbs_step< Model > | |
Basic_gibbs_step< Model > | |
Abstract_hmc_step< Model, CONSTRAINED_TARGET, INCLUDE_ACCEPT_STEP, REVERSIBLE > | |
Basic_hmc_step< Model, CONSTRAINED_TARGET, INCLUDE_ACCEPT_STEP, REVERSIBLE > | |
Real_hmc_step< Model, CONSTRAINED_TARGET, INCLUDE_ACCEPT_STEP, REVERSIBLE > | |
Basic_hmc_step< Model, CONSTRAIN_TARGET, INCLUDE_ACCEPT_STEP, REVERSIBLE > | |
Vector_hmc_step< Model, CONSTRAIN_TARGET, INCLUDE_ACCEPT_STEP, REVERSIBLE > | |
Abstract_mh_step< Model, Proposer > | |
Basic_mh_step< Model, Proposer > | |
Annealing_mh_step< Model, Proposer > | |
Abstract_mh_step< kjb::Vector, typename Mh_model_proposer< kjb::Vector >::Type > | |
Basic_mh_step< kjb::Vector > | |
Abstract_mh_step< Model, Proposer_type > | |
Basic_mh_step< Model, Proposer_type > | |
Abstract_mh_step< SimpleVector, typename Mh_model_proposer< SimpleVector >::Type > | |
Basic_mh_step< SimpleVector > | |
Abstract_mh_step< VectorModel, Mv_gaussian_proposer< VectorModel > > | |
Basic_mh_step< VectorModel, Mv_gaussian_proposer< VectorModel > > | |
Vector_srw_step< VectorModel > | |
Abstract_sampler< Model > | |
Multi_step_sampler< Model > | |
Annealing_sampler< Model > | |
Single_step_sampler< Model > | |
kjb::Abstract_video | |
kjb::Video | |
kjb::psi::Action | |
kjb::psi::Action_descriptor | |
kjb::bbb::Description_info::Activity_info | |
kjb::bbb::Activity_library | |
kjb::bbb::Activity_sequence | |
kjb::bbb::Activity_sequence_prior | |
semantics::Alpha_sampler< T > | |
Annealable< X > | |
Annealing_proposer_wrapper< Proposer, Model > | |
array | |
kjb::Matrix_d< M, N, Transposed > | |
kjb::Vector_d< D > | |
kjb::Vector_d< 2 > | |
kjb::Vector_d< 3 > | |
kjb::bbb::Association | |
kjb::mcmcda::Association_directory | Later |
kjb::bbb::Association_prior | |
kjb::TopoFusion::AutoLayer | RAII approach to the old TopoFusion Layer data structure |
kjb::Axis_aligned_rectangle_2d | Class that represents an axis-aligned 2D rectangle. It is defined in terms of its (2D) center, its width and its height |
kjb::Back_projector | |
kjb::Ground_back_projector | |
kjb::Base_gl_interface | |
kjb::Parametric_camera_gl_interface | |
base_model_archetype | |
vector_model_archetype | |
BaseModel< X > | |
VectorModel< X > | |
Basic_sd_step< Model, REVERSIBLE > | |
kjb::psi::Bbox_noise_likelihood | |
kjb::psi::Bbox_pairwise_likelihood | |
Best_model_recorder< Model > | |
Best_target_recorder< Model > | |
kjb::Beta_binomial_distribution | |
binary_function_archetype | |
model_proposer_archetype< Model > | |
model_recorder_archetype< Model > | |
BinaryFunction | |
ModelProposer< Func, Model > | |
Blob | A simple class that represents a blob |
Blob_detector | A blob detector class. Use operator() to apply to image |
kjb::pt::Body_2d | 2D body information resulting from projecting the 3D body |
kjb::pt::Box_likelihood | Class that represents likelihood of a set of projected boxes given. detections. At the moment it only uses box size and optical flow; in the future, it may be use other data information |
DTLib::CAffine | |
kjb::Calibration_descriptor | |
kjb::pt::Camera_prior | Class that represents the camera prior |
kjb::Canny_edge_detector | Implements the Canny edge detection algorithm |
kjb::Categorical_distribution< T > | A categorical distribution |
kjb::Categorical_distribution< int > | |
kjb::Categorical_distribution< size_t > | |
semantics::Categorical_event_base | Abstract base class for look-up keys |
semantics::Categorical_event< 0 > | |
semantics::Categorical_event< N > | Look-up key class for contingency table |
semantics::Cell | |
semantics::Context_cell_base | |
semantics::Context_cell< T, N > | Class containing conditioning context for marginal cells |
semantics::Marginal_cell_base | |
semantics::Marginal_cell< T, N > | Concrete class for contingency table cell |
semantics::Prior_cell< T > | |
semantics::Cell_traits< T, N > | |
semantics::Cell_traits< semantics::D2_view, 2 > | |
semantics::Cell_traits< T, 1 > | |
DTLib::CFilterbank | |
kjb::Chamfer_transform | |
spear::CharArrayEqualFunc | |
spear::CharArrayHashFunc | |
kjb::Chinese_restaurant_process | |
DTLib::CHistogram< T > | |
DTLib::CImg< T > | |
DTLib::CImg< BYTE > | |
DTLib::CSparsePatImg | |
DTLib::CImg< float > | |
DTLib::CGaussKernel | |
DTLib::CDOG | |
DTLib::CImgVec< T > | |
DTLib::CImgVec< BYTE > | |
DTLib::CCircleMasks | |
kjb::Circle | |
DTLib::CJPEG | |
DTLib::CKMeans | |
kjb::Cloneable | Abstract class to clone this object |
kjb::Perspective_camera | |
kjb::Calibrated_camera | |
kjb::Renderable_model | |
kjb::Parametric_frustum | |
kjb::Parametric_parapiped | |
kjb::Parametric_sphere | |
kjb::Rigid_object | |
kjb::Parametric_camera_gl_interface | |
kjb::Polymesh | Abstract class of connected polygons (faces) forming a mesh. We assume that each edge is shared between exactly two faces, that is to say the mesh has to be fully connected |
kjb::Frustum | Frustum: a polyhedron of which each torso face is a trapezoid and the top and bottom surfaces are polygons |
kjb::Parapiped | Parallelepiped: a hexahedron of which each face is a parallelegram |
kjb::Triangular_mesh | Triangular_mesh: a polygonal mesh of which each face is a triangle |
kjb::Spline_curve | |
kjb::Bezier_curve | |
kjb::Nurbs_curve | |
kjb::Polybezier_curve | |
kjb::Spline_surface | |
kjb::Nurbs_surface | |
kjb::pt::Color_likelihood | Class that represents color likelihood of a set of projected boxes given detections |
kjb::Color_likelihood | Functor that computes the likelihood of a set of projected faces onto an image, using the color distribution of each projected face. More later.. |
kjb::Colormap | |
kjb::Comparable_omap |
- creates an omap from an image that can call compare_omap(compareto) to see how similar it is
|
kjb::pt::Comparator_2d | Comparator for Propagated_2d_info |
kjb::Compare_address< T > | Predicate that returns true if address of element equals given |
kjb::Compare_box_distance | Functor for comparing box distance |
kjb::Line_correspondence::Line_bin::Compare_edge_segment_starting_points | Compare the corresponding Line_bin based on the x position of the starting point of the image edge segment |
kjb::Compare_flow_features | Functor to compare two Feature_pair |
kjb::Correspondence::Point::Compare_Normal_Distance | |
kjb::Correspondence::Matched_point::Compare_Normal_Distance | |
kjb::compare_point_x_location | |
kjb::mcmcda::Compare_tracks< Track > | Functor to compare two tracks. If this were not defined, an association would order its tracks using operator<(pair, pair), which would eventually order by the address of the detection. We use this one to avoid this comparison by address and instead use a value comparison. This way the order will not change every time we read an association |
kjb::pt::Complete_state | Represents the state of an actor at a frame |
Compute_blob | |
Computes | |
kjb::Conditional_distribution< TargetVariable, GivenVariable, DependenceFunc > | A conditional distribution |
Conditional_distribution_proposer< ConditionalDistribution, Model > | |
Constant_parameter_evaluator< Model > | Returns the same result no matter what model is received |
Constrained_target< Model > | Adapts a target distribution to be one with bounds |
kjb::pt::Write_scene_iterator::container_type | Fake container type. Needed for recorder to find the type |
Control_scene | Class that represents a scene plus the control ouptuts; i.e. the model for the control-point trajectory sampler |
kjb::Correspondence | |
DTLib::CTextureScale | |
kjb::psi::Cuboid | |
kjb::psi::Weighted_box | |
Current_log_recorder< Model > | |
Current_model_recorder< Model > | |
kjb::opencv::CV_features_to_track_detector | |
kjb::opencv::CV_term_criteria | |
kjb::bbb::Data | |
deque | |
Recent_model_recorder< Model > | |
Step_log< Model > | |
All_log_recorder< Model > | |
Recent_log_recorder< Model > | |
kjb::bbb::Description | |
kjb::bbb::Description_info | Extract sparse information from description (for write()) |
kjb::bbb::Description_prior | |
kjb::pt::Detection_box | Class that represents a detection bounding box from any source |
kjb::Deva_detection | |
kjb::Deva_facemark | |
kjb::qd::DijkstraPriorityQueue< SATELLITE_TYPE > | Pure virtual interface for priority queue in Dijkstra's algorithm |
kjb::qd::Redblack_subtree_sum< SATELLITE_TYPE > | Balanced binary search tree storing subtree sums in each node |
kjb::qd::StochasticPriorityQueue< SATELLITE_TYPE, POWERLAW_NUM, POWERLAW_DEN > | Priority queue implementing a stochastic extract-near-min method |
kjb::qd::DijkstraPriorityQueue< Sat_tp > | |
kjb::qd::Redblack_subtree_sum< Sat_tp > | |
kjb::qd::DijkstraPriorityQueue< SatLoc > | |
kjb::qd::Redblack_subtree_sum< SatLoc > | |
kjb::pt::Direction_prior | Class that represents the prior distribution of a trajectory |
kjb::Distribution_traits< Distribution > | Generic traits struct for all distributions |
kjb::Distribution_traits< Categorical_distribution< T > > | Traits for the categorical distro |
kjb::Distribution_traits< Chinese_restaurant_process > | |
kjb::Distribution_traits< Log_normal_distribution > | |
kjb::Distribution_traits< Mixture_distribution< Distribution > > | Traits for the mixture distro. Type is the type of the mixed distributions |
kjb::Distribution_traits< MV_gaussian_distribution > | Traits for the multivariate normal. Type is kjb::Vector |
kjb::Distribution_traits< Uniform_sphere_distribution< D > > | Traits for the Uniform_sphere_distribution |
kjb::Distribution_traits< Von_mises_fisher_distribution< D > > | Traits for the Von-mises-fisher distribution |
kjb::TopoFusion::DOrthoQuad | Digital orthoquad buffer |
kjb::qd::DoubleCircle | Parameterized circle in the plane |
kjb::qd::Doubly_connected_edge_list | Data structure for a planar subdivision made by edges |
semantics::Dummy_template_class< M > | |
kjb::Edge | |
kjb::Edge_lines_likelihood | |
kjb::Edge_point | |
kjb::qd::Doubly_connected_edge_list::Edge_record | |
kjb::Edge_set | |
spear::EdgeLexer | |
spear::EdgeParser< T > | |
semantics::Elaboration_tree | Main "Semantic tree" object |
kjb::TopoFusion::Ellipsoid | TopoFusion data structure used to represent an ellipsoid earth |
kjb::Index_range::End_type | |
kjb::bbb::Endpoint | Class that holds information for endpoints |
kjb::tracking::Entity_id | Entity + index; used for file I/O |
kjb::psi::Entity_state | |
semantics::Event_db | Database class to read and count parse tree events |
Event_listener | |
kjb::gui::Interactive_object | |
Null_event_listener | |
semantics::Event_view< T, Traits > | Template class to represent different "views" of syntactic events |
kjb::Every_nth_element< T > | Predicate that returns true every nth call |
spear::Exception | |
exception | |
kjb::Exception | Base class of all exceptions in the jwsc++ library |
kjb::Cant_happen | Object thrown when the program does something thought impossible |
kjb::IO_error | Object thrown when input or output fails |
kjb::psi::File_format_exception | |
kjb::KJB_error | Exception often thrown when wrapped C functions return error codes |
kjb::Missing_dependency | Object thrown when a program lacks required resources or libraries |
kjb::Not_implemented | Object thrown when attempting to use unimplemented functionality |
kjb::Option_exception | Object thrown for exceptions related to command-line options |
kjb::Missing_option | Object thrown when an obligatory command-line option is absent |
kjb::Result_error | Object thrown when a function cannot generate a valid result |
kjb::qd::PixPoint::Unused | Exception thrown if the PixPoint is used while uninitialized |
kjb::Runtime_error | Object thrown when computation fails somehow during execution |
kjb::Divide_by_zero | Object thrown when an division is attempted with a zero divisor |
kjb::Illegal_argument | Object thrown when an argument to a function is not acceptable |
kjb::Dimension_mismatch | Object thrown when an argument is of the wrong size or dimensions |
kjb::Index_out_of_bounds | Object thrown when an index argument exceeds the size of a container |
kjb::Resource_exhaustion | Object thrown if a resource allocation failed (memory, fp, etc.) |
kjb::Serialization_error | Object thrown when serialization or deserialization fails |
kjb::Stack_overflow | Object thrown if a finite size stack is full and pushed farther |
kjb::Stack_underflow | Object thrown if stack is empty and popped |
Expectation_recorder< Model, Value > | |
kjb::mcmcda::Experiment_directory | Later |
kjb::pt::Face_2d | 2D face information resulting from projecting the 3D head/face |
Face_data | |
kjb::Face_detection | |
kjb::pt::Face_direction_prior | Class that represents the prior distribution of the face direction |
kjb::pt::Face_flow_likelihood | Class to compute face optical flow likelihood |
kjb::qd::Doubly_connected_edge_list::Face_record | |
kjb::pt::Facemark_likelihood | Class to compute facemark likelihood |
kjb::Feature_histogram | |
kjb::pt::Feature_score | |
Features | Allows to manipulate basic 2d image features (edges, fitted line segments and manhattan worl). This is mostly useful for Manhattan world scenes so it might be renamed. This class contains the following features: |
kjb::Fftw_convolution_2d | A class for performing 2d convolution using the FFTW library |
kjb::Fftw_image_convolution | This is a simple adaptation of Fftw_convolution_2d to Image input |
kjb::FFTW_Plan2d< T, U > | RAII class to manage an FFTW plan |
kjb::Fh_type | |
kjb::File_Ptr | RAII wrapper on stdio.h FILE pointers (use a derived class though) |
kjb::File_Ptr_Append | RAII wrapper on FILE* used to append a file (write only at the end) |
kjb::File_Ptr_Read | RAII wrapper on FILE* used to read a file |
kjb::File_Ptr_Read_Plus | RAII wrapper on FILE* opened with mode "r+" to read and write |
kjb::File_Ptr_Smart_Read | This class transparently opens gzipped or bzip2-ed files |
kjb::File_Ptr_Write | RAII wrapper on a FILE* used to write to a file |
kjb::Temporary_File | This class safely opens a temporary file in TEMP_DIR (usually /tmp) |
kjb::Filter | Filter class |
kjb::Foreground_mask | |
kjb::psi::Frame_likelihood | |
Gaussian_random_walk_proposer | |
Gaussian_scale_space | |
Gaussian_scale_space_generator | |
kjb::Generic_const_matrix_view< Matrix_type > | |
kjb::Generic_const_vector_view< Vector_type > | |
kjb::Generic_matrix_view< Matrix_type > | |
kjb::tracking::Generic_trajectory_element< T > | Represents an element of a trajectory of a particular entity |
kjb::Generic_vector_view< Vector_type > | |
kjb::Geometric_context | |
kjb::Get_address< T > | Functor that returns the address of a given object |
Get_model_parameter< Model > | Gets the specified parameter of a model. For now, we assume all parameters are type double |
Gibbs_model_proposer< Model > | |
kjb::mcmcda::Gibbs_proposer< Track, Lhood > | Gibbs proposal mechanism for tracking. Complies with Gibbs proposer concept |
kjb::GL_Polygon_Renderer | |
kjb::GL_Polymesh_Renderer | |
kjb::opengl::Glew | |
kjb::Glut_parapiped | |
kjb::Glut_perspective_camera | |
GLUT_polymesh | |
kjb::Glut_polymesh | |
kjb::pt::Gradient_adapter< G > | Wraps Scene_gradient to work with ergo::hmc_step |
kjb::bbb::Group | Group |
gsl_matrix | |
kjb::Gsl_multifit_fdf | |
gsl_multifit_function_fdf | |
kjb::Gsl_Multimin_f | Wrapper for GSL's multidimensional minimizer, without using gradient |
kjb::Generic_multimin< T > | |
kjb::Gsl_Multimin_fdf | Wrapper for GSL's multidimensional minimizer, when you have gradient |
gsl_multimin_function | |
gsl_multimin_function_fdf | |
kjb::Gsl_Qrng_basic< KIND > | Wrapper for one of GSL's quasi-random generators |
kjb::Gsl_Qrng_basic< GSL_QRNG_HALTON > | |
kjb::Gsl_Qrng_Halton | Quasi-random generator using the algorithm of Halton |
kjb::Gsl_Qrng_basic< GSL_QRNG_NIEDER > | |
kjb::Gsl_Qrng_Niederreiter | Quasi-random generator using the algorithm of Bratley et al |
kjb::Gsl_Qrng_basic< GSL_QRNG_RVSHALTON > | |
kjb::Gsl_Qrng_Rvs_Halton | Quasi-random generator using the algorithm of Vandewoestyne et al |
kjb::Gsl_Qrng_basic< GSL_QRNG_SOBOL > | |
kjb::Gsl_Qrng_Sobol | Quasi-random generator using the algorithm of Antonov and Saleev |
kjb::Gsl_ran_discrete | Randomly sample discrete events with an empirical distribution |
kjb::Gsl_rng_basic< KIND > | Basic RAII wrapper for GNU GSL random number generators |
Gsl_rng_cmrg | Random number generator using L'Ecuyer's 1996 algorithm. This implements the Combined Multiple Recursive Generator algorithm of L'Ecuyer (1996). Period is 10 ** 56. Defined using macro Gsl_rng_template |
Gsl_rng_gfsr4 | Random number generator using a four-tap XOR using a shift register. This uses Ziff's offsets (1998) and is very fast |
Gsl_rng_mrg | Random number generator using 1993 algorithm of L'Ecuyer et al. This implements the Multiple Recursive Generator algorithm of L'Ecuyer et al. (1993). Period is 10 ** 46. Defined using macro Gsl_rng_template |
Gsl_rng_mt19937 | Random number generator using the "Mersenne Twister" algorithm. This implements the "Mersenne Twister" of Matsumoto and Nishimura. The period is about 10 ** 6000. This is an all-around good PRNG. Defined using macro Gsl_rng_template |
Gsl_rng_ranlxd1 | Random number generator using the "RANLUX" algorithm, 48 bits, lvl. 1 This implements the "RANLUX" algorithm of Luescher at double precision. This is a "luxury random number" algorithm, i.e., slow. This one is "level 1" so it's not as decorrelated as level 2. Period is 10 ** 171. Defined using macro Gsl_rng_template |
Gsl_rng_ranlxd2 | Random number generator using the "RANLUX" algorithm, 48 bits, lvl. 1 This implements the "RANLUX" algorithm of Luescher at double precision. This is a "luxury random number" algorithm, i.e., slow. This one is "level 2" so it's the most decorrelated. Period is 10 ** 171. Defined using macro Gsl_rng_template |
Gsl_rng_ranlxs0 | Random number generator using the "RANLUX" algorithm, 24 bits. This implements the "RANLUX" algorithm of Luescher at single precision, i.e., meant for a float not a double. This is a "luxury random number" algorithm, i.e., slow. Nevertheless this one is "level 0" so it's the entry-level luxury model. Period is 10 ** 171. Defined using macro Gsl_rng_template |
Gsl_rng_ranlxs1 | Random number generator using the "RANLUX" algorithm, 24 bits. This implements the "RANLUX" algorithm of Luescher at single precision, i.e., meant for a float not a double. This is a "luxury random number" algorithm, i.e., slow. This one is "level 1" so it's the mid-level luxury model. Period is 10 ** 171. Defined using macro Gsl_rng_template |
Gsl_rng_ranlxs2 | Random number generator using the "RANLUX" algorithm, 24 bits. This implements the "RANLUX" algorithm of Luescher at single precision, i.e., meant for a float not a double. This is a "luxury random number" algorithm, i.e., slow. This one is "level 2" so it's the top-level luxury model. Period is 10 ** 171. Defined using macro Gsl_rng_template |
Gsl_rng_taus2 | Random number generator using Tausworthe's algorithm. This is L'Ecuyer's version of Tausworthe's algorithm (or something like that). Period is 10 ** 26. Defined using macro Gsl_rng_template |
gsl_vector | |
kjb::Gsl_Vector | RAII wrapper for GSL vector objects |
kjb::pt::Head | Simple struct representing a head |
kjb::Heartbeat | A class for for indicating the status of slow-moving loops |
kjb::Histogram | A class that represents a histogram of data. ATM, the data must be doubles |
kjb::Histogram_2d | |
kjb::Identity< T > | Identity function |
kjb::Matrix_d< M, N, Transposed >::if_then_< condition, value1, value2 > | |
kjb::Matrix_d< M, N, Transposed >::if_then_< false, value1, value2 > | |
kjb::Image | Wrapped version of the C struct KJB_image |
kjb::Opengl_framebuffer_image | |
kjb::Feature_histogram::Image_dart | |
kjb::Increase_by< T > | Generator that increases (using +=) itself by the given value everytime it is called |
kjb::Increment< T > | Generator that increments (++) its state everytime it is called. Useful for creating sequences of contigous values |
kjb::Independent_edge_points_likelihood | |
Independent_gaussian_proposer< SimpleVector > | |
kjb::Index_less_than< T > | Predicate that compares the kth element of a indexable type |
kjb::Index_range | |
kjb::pt::Input_directory | Represents the input directory for the people tracking project |
kjb::Int_matrix | This class implements matrices, in the linear-algebra sense, restricted to integer-valued elements |
kjb::Int_vector | This class implements vectors, in the linear-algebra sense, restricted to integer-valued elements |
kjb::Integral_flow | |
kjb::Ned13_one_degree_grid::IntegralLL | Integer-valued, latitude-style and longitude-style coordinates |
kjb::bbb::Intentional_activity | |
kjb::Interval_sequence | |
iterator | |
kjb::circular_iterator< iterator > | |
kjb::const_circular_iterator< const_iterator > | |
kjb::pt::Write_scene_iterator | Record a series of scenes to a directory |
kjb::qd::Redblack_subtree_sum< SATELLITE_TYPE >::const_iterator | Iterator class for a tree – lets you access node locators |
kjb::Word_list::const_iterator | Iterator class used to traverse and read the list |
kjb::Kriging_interpolator | Class to interpolate elevation values using Gaussian processes |
kjb::TopoFusion::layer | Definition used for layer |
kjb::mcmcda::Likelihood< Track > | Computes the GP-based likelihood of an association |
kjb::bbb::Likelihood | |
Line | |
kjb::Line | Parametric representation of a 2D line in terms of three parameters (a,b,c) (as in ax+by+c = 0) |
kjb::Line_correspondence::Line_bin | |
kjb::Line_correspondence | |
kjb::Log_normal_distribution | Log-normal distribution |
kjb::Manhattan_corner | |
kjb::Manhattan_corner_segment | |
kjb::Manhattan_segment | A manhattan segment defined by a line segment and the vanishing point it converges to |
kjb::Manhattan_world | This class contains the three orthogonal vanishing points defining a Manhattan scene, where most or all planes are aligned with three main orthogonal directions. This class optionally contains a set of segments from the scene, assigned to the correct vanishing point |
map | |
kjb::tracking::Generic_trajectory_map< T > | Represents a set of trajectories; it is a map from entity to trajectory |
kjb::Correspondence::Matched_point | |
DTLib::MATFILE | |
kjb::Matrix | This class implements matrices, in the linear-algebra sense, with real-valued elements |
kjb::Matrix_stream_io | Static functions to read and write matrix classes with iostream |
kjb::Matrix_traits< value_type > | |
kjb::Matrix_traits< double > | |
kjb::Matrix_traits< int > | |
kjb::maximum< T > | |
Mh_model_proposer< Model > | |
Mh_model_proposer< kjb::Vector > | |
Mh_model_proposer< SimpleVector > | |
ergo::mh_proposal_result | |
Mh_proposal_result | Indicates the result of an MH proposal. It is simply a pair of probabilities, forward and backward |
kjb::minimum< T > | |
kjb::Mixture_distribution< Distribution > | This class implements a mixture distribution. In other words, it is the sum of a finite number of fractions of distributions of the same type (with different parameters) |
kjb::psi::Model | |
Model_dimension< Model > | Returns the dimension of the model |
Model_edge | |
kjb::psi::Model_evaluator | |
kjb::psi::Cylinder_world_likelihood | |
Model_evaluator< Model > | |
Model_parameter_evaluator< Model > | |
Model_recorder< Model > | |
ModelRecorder< X > | |
Modulo_recorder< Recorder > | |
Move_model_parameter< Model > | Moves the specified parameter of a model. For now, we assume all parameters are type double |
Move_model_parameter_as_plus< Model > | Default move function; uses '+' |
Multi_model_recorder< Model > | |
Multi_proposer_proposer< Model > | |
multimap | |
kjb::mcmcda::Generic_track< Detection_box > | |
kjb::pt::Target | Class that represents a target moving through space |
kjb::mcmcda::Generic_track< E > | A class that represents a generic MCMCDA track |
kjb::Mutex_lock | Simple RAII class to grab and release a mutex |
kjb::MV_gaussian_distribution | Multivariate Gaussian (normal) distribution |
Mv_gaussian_proposer< VectorModel > | |
kjb::MV_normal_on_normal_dependence | Represents the dependence between X and Y in p(x | y), where (x,y) is a multivariate normal |
kjb::Ned13_caching_reader | Interface to an elevation-info object that caches its NED13 grids |
kjb::Ned13_bilinear_reader | Support NED 13 elevation queries using bilinear interpolation |
kjb::Ned13_gp_reader | |
kjb::Ned13_nearest_se_neighbor_reader | Support NED 13 elevation queries by using nearest southeast neighbor |
kjb::Ned13_grid_cache | This caches a bunch (potentially) of one-degree grids for you |
kjb::Ned13_one_degree_grid | Storage for a single NED13 grid tile, plus convenient access |
negative_binomial | |
kjb::Geometric_distribution | |
kjb::Normal_on_normal_dependence | Represents the dependence between X and Y in p(x | y), where (x,y) is a bivariate normal |
Multi_step_sampler< Model >::null_deleter | |
Null_recorder< Model > | |
Callback_recorder< Model > | |
Null_recorder< double > | |
kjb::psi::Progress_recorder | |
Null_value | |
Numerical_gradient< Model > | Approximates the gradient and/or curvature of a target distribution, evaluated at a certain location. The user must provide the mechanisms to change the model (see constructor) |
Real_numerical_gradient< Model > | Approximates the gradient of a target distribution, evaluated at a certain location. The model in question must be a vector model |
Vector_numerical_gradient< Model > | Approximates the gradient of a target distribution, evaluated at a certain location. The model in question must be a vector model |
kjb::Offscreen_buffer | Offscreen rendering buffer |
kjb::Omap_computer | |
kjb::Omap_segment | |
kjb::opengl::Opengl_callable | |
kjb::OpenSSL_EVP | Generic OpenSSL hasher class, the base class for specific derivations |
kjb::MD5 | Message Digest 5 computation, using OpenSSL code |
kjb::pt::Optical_flow_likelihood | Class to compute face optical flow likelihood |
kjb::pt::Optimize_likelihood | Approximate complete-data likelihood via HMC optimziation |
Ostream_recorder< Recorder > | |
kjb::pt::Output_directory | Represents the output directory for the PT tracking project |
spear::Pair< T1, T2 > | |
kjb::Palette | Construct some colors, for visualizing grids of numbers |
kjb::bbb::Parameter_prior | |
spear::Parameters | |
kjb::psi::Person_flow_blob | A class represent the blob detection based on the optical flow magnitude images |
kjb::bbb::Physical_activity | |
Pixel | |
kjb::PixelHSVA | Alternative Pixel using hue, saturation, value, and opacity (alpha) |
kjb::PixelRGBA | Wrapped version of the C struct Pixel, with Alpha (opacity) |
kjb::pt::Pixel_move | Functor designed to move 3D points by pixels in image plane |
kjb::qd::PixPath | Representation of a sequence of pixel coordinates |
kjb::qd::PixPath_expander | Expand, if possible, a PixPath to fill a specified minimum size |
kjb::qd::PixPathAc | This is like PixPath except that it has an arclength cache, for teh performance |
kjb::qd::PolyPath | Open polygonal path with a tangent at each point |
kjb::qd::PixPoint | Representation of an (x,y) pair of pixel coordinates |
kjb::qd::PixPoint_line_segment | Basic line segment when endpoints are PixPoints (int coords) |
kjb::Correspondence::Point | |
kjb::Polymesh_Plane | This class contains a Vector of plane parameters, a vector of the face indices that lie in the plane, and the polymesh that the faces are from. The plane parameters are the coefficients of a plane of the form ax + by + cz + d = 0 |
kjb::pt::Position_prior | Class that represents the prior distribution of a trajectory |
Posterior< Model > | Generic posterior class |
kjb::pt::Posterior_detail_recorder< OutputIterator > | Records the details about the posterior |
kjb::mcmcda::Prior< Track > | Computes the prior of an MCMCDA association |
kjb::pt::Propagated_2d_info | Propagated 2D information using optical flow |
kjb::pt::Propose_person_size | Proposal distribution/mechanism for the size of targets |
kjb::mcmcda::Proposer< Track > | |
kjb::psi::Psi_body_part | Body parts |
kjb::psi::Psi_step_size | |
kjb::TopoFusion::pt | Definition for a TopoFusion pt |
kjb::Pthread_attr | RAII class to manage an object of type kjb_pthread_attr_t |
kjb::Pthread_mutex | Dynamically allocated mutex: unlock before you destroy it! |
kjb::Pthread_locked_mutex | Same as Pthread_mutex, but starts off in "locked" state |
kjb::Quaternion | |
kjb::Ransac_line_fitting | |
kjb::qd::RatPoint | Very basic structure to represent X, Y points with rational coords |
kjb::qd::RatPoint_line_segment | Closed line segment with rational coords |
spear::RCIPtr< T > | |
spear::RCIPtr< Model > | |
spear::RCIPtr< spear::BankEdge > | |
spear::RCIPtr< spear::Lexicon > | |
spear::RCIPtr< spear::spear::Tree > | |
spear::RCObject | |
spear::BankEdge | |
spear::Edge | |
spear::Lexem | |
spear::Lexicon | |
spear::Model | |
spear::Pattern | |
spear::StringMapEntry< T > | |
spear::Tokenizer | |
spear::Trainer | |
spear::Tree | |
kjb::Readable | Abstract class to read this object from an input stream |
kjb::Circle_in_3d | |
kjb::Color_histogram | Class to compute an RGB colour histogram over an image or a rectangular portion of it. The histogram is normalized. We use the same number of bins for each of the channels (r,g,b). It is easy to extend this class so that it computes such histogram over a segment of a shape other than rectangular |
kjb::Corner | Class to manipulate a 2D corner. The corener is defined in terms of a set of line segments all intersecting at a point in the image, which is the corner position. No consistency controls are performed here |
kjb::Cylinder | |
kjb::Cylinder_section | Cylinder_section: a section of a cylinder, specified by angle and position |
kjb::Edge_segment_set | Class to manipulate a set of edge segments |
kjb::Features_manager | |
kjb::Hog_responses | |
kjb::Learned_discrete_prior | This class creates a histogram of a list of points and stores the number of bins in num_bins, the maximum and minimum values allowed in histo_max and histo_min, respectively, and the count of the number of points in each bin in histo_bins, which is a Vector of size num_bins |
kjb::Line_segment | Class to manipulate a line segment The class is parametrized in terms the position of the centre, its length and orientation. This is thus compatible with the output of the Berkeley edge detector. We store also the start point, the end point and the line parameters describing this line segment (for more details on how the line parameters work, please see the class line). This is redundant information, but it is convenient to have all these parameters precomputed and at hand |
kjb::Collinear_segment_chain | Represent a collinear line segment, a collinear line segment is inherited from an Line_segment |
kjb::Edge_segment | |
kjb::Model_edge | |
kjb::Line_segment_set | Class to manipulate a set of line segments |
kjb::Manhattan_hog | |
kjb::Parametric_frustum | |
kjb::Parametric_parapiped | |
kjb::Parametric_sphere | |
kjb::Perspective_camera | |
kjb::Polygon | |
kjb::Polymesh | Abstract class of connected polygons (faces) forming a mesh. We assume that each edge is shared between exactly two faces, that is to say the mesh has to be fully connected |
kjb::Vanishing_point | A vanishing point for a set of parallel lines in an image |
Real_sd_step< Model, REVERSIBLE > | |
kjb::Rectangle_2d | Class that represents an axis-aligned 2D rectangle. It is defined in terms of its (2D) center, its width and its height |
kjb::Renderable | Abstract class to render this object with GL |
kjb::Abstract_renderable | |
kjb::Generic_renderable | |
kjb::Mv_generic_renderable | |
kjb::Renderer_renderable | |
kjb::Polygon | |
kjb::Polymesh | Abstract class of connected polygons (faces) forming a mesh. We assume that each edge is shared between exactly two faces, that is to say the mesh has to be fully connected |
kjb::Generic_renderer | |
kjb::Renderer | |
kjb::Solid_renderer | |
kjb::Wire_occlude_renderer | |
kjb::Wire_renderer | |
kjb::gui::Selectable | |
kjb::gui::Interactive_object | |
kjb::Mv_renderable | Abstract class to render an object that has many possible views |
kjb::Mv_generic_renderable | |
kjb::Mv_solid_render_wrapper | |
kjb::Mv_wire_occlude_render_wrapper | |
kjb::Mv_wire_render_wrapper | |
kjb::RenderableObject< X > | |
kjb::Right_Triangle_Pair | |
kjb::Rotation_axis | |
kjb::pt::Sample_scenes | Use HMC to draw samples from the scene posterior using HMC |
Sampler_step< Model > | |
kjb::pt::Scene | Class that represents a full scene in the PT universe |
kjb::pt::Scene_adapter | Adapts a Scene into a VectorModel for HMC sampling |
kjb::pt::Scene_gradient | Wrapper for generic gradient function |
kjb::pt::Scene_hessian | Wrapper for generic hessian function |
kjb::pt::Scene_posterior | Posterior distribution of a scene |
kjb::pt::Scene_posterior_ind | Posterior adapter to work with independent gradient computation |
kjb::pt::Scene_recorder | Record a series of scenes to a directory |
kjb::Scope_guard | |
kjb::TopoFusion::seg | Old TopoFusion data structure for a sequence of pt structures |
kjb::Segment_pair | |
kjb::Select_coordinate< V > | Selects a coordinate from a vector type |
semantics::Sem_lexer | |
semantics::Semantic_data_base | Abstract base class of Semantic Data template |
semantics::Semantic_data< T, Traits > | Concrete semantic data class for storing hash codes about nodes |
semantics::Semantic_elaboration | Base class for semantic elaborations |
semantics::Nonterminal_elaboration< T, Traits > | |
semantics::Terminal_elaboration< T, Traits > | Class representing semantic nodes at the leaves of trees |
semantics::Semantic_step_proposal | |
semantics::Semantic_traits< T > | Traits class storing information specific to given elaboration types |
semantics::Semantic_traits< Binary_predicate > | |
semantics::Semantic_traits< Binary_relation_primitive > | |
semantics::Semantic_traits< Category_primitive > | |
semantics::Semantic_traits< Color_primitive > | |
semantics::Semantic_traits< Null_primitive > | |
semantics::Semantic_traits< Semantic_object > | |
semantics::Semantic_traits< Size_primitive > | |
semantics::Semantic_traits< Unary_predicate > | |
semantics::Semantic_traits< Unary_relation_primitive > | |
semantics::Semspear_tree | The main syntactic tree object for semantic parsing |
semantics::Semspear_tree_parser< T > | |
semantics::Sentence_sem | |
kjb::Sequence | |
kjb::SerializableConcept< X > | |
Serialize_recorder< Recorder_type > | |
set | |
kjb::mcmcda::Association< Target > | |
kjb::mcmcda::Association< Track > | A class that represents a MCMCDA association |
Set_model_parameter< Model > | Sets the specified parameter of a model. For now, we assume all parameters are type double |
Simple_adaptive_mh_step< SimpleVector > | |
Simple_adaptive_mh_step< kjb::Vector > | |
Generic_adaptive_mh_step< Model > | |
kjb::psi::Simple_simulator | |
kjb::SimpleVector< X > | |
Single_dimension_proposer< Model > | |
kjb::Fftw_convolution_2d::Sizes | Utility aggregate stores all sizes – rarely used by caller |
kjb::Solid_renderable | Abstract class to render this object with GL |
kjb::Abstract_renderable | |
kjb::Sphere | |
kjb::Spot_detector | A spot detector functor, comparable to a blob detector |
ST_SPHERE | |
kjb::psi::Start_state | |
static_visitor | |
kjb::bbb::Get_end | |
kjb::bbb::Get_name | |
kjb::bbb::Get_start | |
kjb::bbb::Get_trajectories | |
kjb::bbb::Output_activity | |
kjb::bbb::Sample_tree | |
Step_result< Model > | Structure for returning results of a single sampling move |
spear::StringMap< T > | |
spear::StringMap< bool > | |
spear::StringMap< int > | |
spear::StringMap< String > | |
kjb::Svd | Tuple that computes a singular value decomposition of a matrix |
kjb::qd::SvgWrap | Class used to render a PixPath as an SVG polygonal path picture |
kjb::Temporary_Directory | This class creates a temporary directory under TEMP_DIR (usu. /tmp) |
kjb::Temporary_Recursively_Removing_Directory | Create a temp directory that destroys itself with "rm -rf" command |
Quaternion::This | Sets the rotation mode of this rigid object. All euler modes are supported (XYZ, ZYZ, etc). All modes ar supported. For further details see adequately tested only in the case of mode = XYZR |
kjb::TopoFusion::tile_entry | Data structure for downloaded UTM tiles, like a pt |
kjb::TopoFusion::Tile_manager | RAII tool for opening and closing the DOQ master index |
kjb::to_ptr | Convert to a pointer |
semantics::Token_map | |
semantics::Lexicon_db | |
semantics::Nonterminal_db | |
semantics::Semantic_db | |
kjb::TopoFusion::track | Old TopoFusion data structure: metadata for a seg |
kjb::psi::Track_metrics | |
kjb::bbb::Traj_set | |
kjb::bbb::Trajectory | |
kjb::bbb::Trajectory_prior | |
kjb::Transformable | Abstract class to apply a linear transformation to this object |
kjb::Rigid_object | |
semantics::Tree_event | |
semantics::Semantic_step_event | |
semantics::Head_semantic_event | |
semantics::Mod_semantic_event | |
semantics::Null_semantic_event | |
semantics::Syntactic_event | |
semantics::Dependency_event | |
semantics::Punctuation_event | |
semantics::Root_event | |
semantics::TOP_event | |
semantics::Unary_event | |
triangulateio | |
kjb::Turntable_camera | |
unary_function | |
kjb::qd::PixPoint::Is_inbounds | Predicate functor tests whether a PixPoint is in a bounding box |
unary_function_archetype | |
model_evaluator_archetype< Model > | |
UnaryFunction | |
ModelEvaluator< Func, Model > | |
kjb::Uniform_sphere_distribution< D > | |
unordered_map | |
spear::HashMap< const Char *, spear::RCIPtr< spear::StringMapEntry< bool > >, spear::spear::CharArrayHashFunc, spear::spear::CharArrayEqualFunc > | |
spear::HashMap< const Char *, spear::RCIPtr< spear::StringMapEntry< int > >, spear::spear::CharArrayHashFunc, spear::spear::CharArrayEqualFunc > | |
spear::HashMap< const Char *, spear::RCIPtr< spear::StringMapEntry< String > >, spear::spear::CharArrayHashFunc, spear::spear::CharArrayEqualFunc > | |
spear::HashMap< const Char *, spear::RCIPtr< spear::StringMapEntry< T > >, spear::spear::CharArrayHashFunc, spear::spear::CharArrayEqualFunc > | |
spear::HashMap< K, V, F, E > | |
Updatable< X > | |
kjb::Vanishing_point_detector | This class computes the position of the three vanishing points from a set of line segments. The ass |
vector | |
All_model_recorder< Model > | |
kjb::mcmcda::Data< Detection_box > | |
kjb::pt::Box_data | |
kjb::tracking::Generic_trajectory< Body_2d > | |
kjb::tracking::Generic_trajectory< Complete_state > | |
kjb::tracking::Generic_trajectory< Face_2d > | |
kjb::mcmcda::Data< Element > | A class that holds data for the tracking problem |
kjb::psi::Deva_skeleton_boxes | |
kjb::psi::Psi_skeleton | Skeleton class, a vector of body parts |
kjb::psi::Skeleton_detection | Skeleton class, a vector of body parts |
kjb::psi::Track_frame_metrics | |
kjb::tracking::Generic_trajectory< T > | Represents a trajectory. Vector of optionals to trajectory elements |
kjb::Vector | This class implements vectors, in the linear-algebra sense, with real-valued elements |
kjb::Vector_adapter< Vec > | Default adapter for the hessian function |
Vector_sd_step< Model, REVERSIBLE > | |
kjb::Vector_stream_io | Functions to read and write vector classes with streams |
kjb::qd::Doubly_connected_edge_list::Vertex_record | |
kjb::Video_frame | |
semantics::View_traits< T > | |
semantics::View_traits< D1_event > | |
semantics::View_traits< D2_event > | |
semantics::View_traits< Hsem_event > | |
semantics::View_traits< Msem_event > | |
semantics::View_traits< PCC1_event > | |
semantics::View_traits< PCC2_event > | |
semantics::View_traits< S1_event > | |
semantics::View_traits< S2_event > | |
semantics::View_traits< U_event > | |
Viewing_recorder< Recorder, Updater > | |
kjb::pt::Visibility | Represents the information regarding visibility of an actor at a given frame and given all other actors |
kjb::bbb::Visualizer | Visualize a description and the corresponding data |
kjb::Von_mises_fisher_distribution< D > | |
kjb::TopoFusion::waypoint | Definition used for waypoint |
kjb::Weight_array< D > | Forward declarations |
kjb::Wire_occlude_renderable | Abstract class to render this object with GL as an occluded wire-frame into the depth buffer, to hide unseen lines |
kjb::Abstract_renderable | |
kjb::Wire_renderable | Abstract class to render this object with GL as a wire-frame |
kjb::Abstract_renderable | |
spear::Word | |
kjb::Word_list | Wrapper for the libKJB type Word_list (useful for globs) |
kjb::Writeable | Abstract class to write this object to an output stream |
kjb::Circle_in_3d | |
kjb::Color_histogram | Class to compute an RGB colour histogram over an image or a rectangular portion of it. The histogram is normalized. We use the same number of bins for each of the channels (r,g,b). It is easy to extend this class so that it computes such histogram over a segment of a shape other than rectangular |
kjb::Corner | Class to manipulate a 2D corner. The corener is defined in terms of a set of line segments all intersecting at a point in the image, which is the corner position. No consistency controls are performed here |
kjb::Cylinder | |
kjb::Edge_segment_set | Class to manipulate a set of edge segments |
kjb::Features_manager | |
kjb::Hog_responses | |
kjb::Learned_discrete_prior | This class creates a histogram of a list of points and stores the number of bins in num_bins, the maximum and minimum values allowed in histo_max and histo_min, respectively, and the count of the number of points in each bin in histo_bins, which is a Vector of size num_bins |
kjb::Line_segment | Class to manipulate a line segment The class is parametrized in terms the position of the centre, its length and orientation. This is thus compatible with the output of the Berkeley edge detector. We store also the start point, the end point and the line parameters describing this line segment (for more details on how the line parameters work, please see the class line). This is redundant information, but it is convenient to have all these parameters precomputed and at hand |
kjb::Line_segment_set | Class to manipulate a set of line segments |
kjb::Manhattan_hog | |
kjb::Parametric_frustum | |
kjb::Parametric_parapiped | |
kjb::Parametric_sphere | |
kjb::Perspective_camera | |
kjb::Polygon | |
kjb::Polymesh | Abstract class of connected polygons (faces) forming a mesh. We assume that each edge is shared between exactly two faces, that is to say the mesh has to be fully connected |
kjb::Vanishing_point | A vanishing point for a set of parallel lines in an image |