Object Detection on Lidar Point Clouds
Detect and fit oriented bounding boxes around objects in lidar point clouds and use them for object tracking or lidar labeling workflows. Design, train, and evaluate robust detectors such as PointPillars networks and generate C/C++ or CUDA code for target hardware.
Cross-calibrate lidar and camera sensors to fuse camera and lidar data. Use the Lidar Camera Calibrator app to detect, extract, and visualize checkerboard features from images and lidar point clouds. Estimate the rigid transformation matrix between the camera and the lidar using feature detection results.
Lidar Registration and Simultaneous Localization and Mapping (SLAM)
Register lidar point clouds by extracting and matching fast point feature histogram (FPFH) descriptors or using segment matching. Implement 3D SLAM algorithms by stitching together lidar point cloud sequences from ground and aerial lidar data.