Vital Algorithms

Vital contains a collection of pure virtual algorithm interfaces to extend with specific methodology. There is an algorithm abstract base class for all algorithm implementations. Next there is an intermediate algorithm template that is used to provide abstract algorithm definitions for specific functionality.

Provided Algorithm Base Classes

Vital provides a collection of algorithm base classes that represent specific functionality and are instantiated as KWIVER arrows. KWIVER end-users may use a provided algorithm’s arrow implementation, create their own implementation, and even create a new algorithm template to define new algorithm functionality previously undefined in kwiver.

analyze_tracks

class kwiver::vital::algo::analyze_tracks Abstract base class for writing out human readable track statistics. Inherits from kwiver::vital::algorithm_def< analyze_tracks > Subclassed by kwiver::vital::algorithm_impl< analyze_tracks, vital::algo::analyze_tracks >

analyze_tracks	bundle_adjust	close_loops	compute_ref_homography
compute_stereo_depth_map	compute_track_descriptors	convert_image	detect_features
detected_object_filter	detected_object_set_input	detected_object_set_output	draw_detected_object_set
draw_tracks	dynamic_configuration	estimate_canonical_transform	estimate_essential_matrix
estimate_fundamental_matrix	estimate_homography	estimate_similarity_transform	extract_descriptors
feature_descriptor_io	filter_features	filter_tracks	formulate_query
image_filter	image_io	image_object_detector	initialize_cameras_landmarks
match_features	optimize_cameras	refine_detections	track_descriptor_set_input
track_descriptor_set_output	track_features	train_detector	triangulate_landmarks