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