Calibration algorithms: These algorithms calibrate the LiDAR sensor to correct for systematic errors or drift.
2023/08/07
Quality assessment algorithms: These algorithms evaluate the quality of the point cloud data, such as accuracy, completeness, or consistency.
2023/07/31
Visualization algorithms: These algorithms generate visualizations of the point cloud data to aid in human interpretation.
2023/07/24
Compression algorithms: These algorithms compress the point cloud data to reduce storage or transmission bandwidth.
2023/07/17
Change detection algorithms: These algorithms compare multiple point clouds acquired at different times to detect changes in the scene, such as new objects or changes in object position.
2023/07/10
Anomaly detection algorithms: These algorithms detect abnormal or unexpected patterns in the point cloud data that may indicate anomalous behavior or events.
2023/07/03
Scene understanding algorithms: These algorithms analyze the point cloud data to infer higher-level properties of the scene, such as the layout or functionality of the environment.
2023/06/26
Object tracking algorithms: These algorithms track objects of interest over time using multiple point clouds acquired at different time steps.
2023/06/19
Object detection algorithms: These algorithms identify objects of interest in the point cloud data, such as cars, pedestrians, or traffic signs.
2023/06/12
Segmentation refinement algorithms: These algorithms refine segmentation results by incorporating additional cues, such as texture or context.
2023/06/06
Contour detection algorithms: These algorithms identify contours or boundaries of objects in the point cloud data.
2023/05/31
Normal estimation algorithms: These algorithms estimate surface normals at each point in the point cloud data to capture local surface geometry.
2023/05/22