Learn how to use MATLAB to process lidar sensor data for ground, aerial and indoor lidar processing application. You will learn how to use MATLAB to:

Import and visualize live and recorded lidar data
Apply deep learning to lidar data
Calibrate lidar and cameras
Track objects in lidar
Create 3D maps and terrain maps using SLAM
Generate C/C++ and GPU Code
Highlights Include:

Lidar Labeler App: Interactive, semiautomated, and custom automated labeling of lidar point clouds
LidarCamera Calibration: Calibrate lidar and camera sensors to estimate crosssensor coordinate transform
Deep Learning for Lidar Point Cloud Processing: Use deep learning networks to detect and segment objects in lidar point cloud data
Shape Fitting: Fit shape and track detected objects in a lidar point cloud sequence
Feature Matching: Extract and match lidar point cloud features
Lidar Object Tracking
Simulating Lidar Sensor Data
2D Lidar Processing: Simulate and process 2D laser scan data and estimate the pose between two scans
Velodyne LiDAR Streaming: Connect and stream lidar point clouds from Velodyne LiDAR sensors
Lidar File Readers: Support for Ibeo sensor, LAS, and LAZ file formats
Code generation for CPU and GPU
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Minhaj Falaki – Product Manager, MathWorks India
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לפייסבוק:   / matlabisrael  
ללינקדין:   / 1774805