Lidar Processing with MATLAB

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 3-D maps and terrain maps using SLAM
Generate C/C++ and GPU Code
Highlights Include:

Lidar Labeler App: Interactive, semi-automated, and custom automated labeling of lidar point clouds
Lidar-Camera Calibration: Calibrate lidar and camera sensors to estimate cross-sensor 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
2-D Lidar Processing: Simulate and process 2-D 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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לנושאים נוספים ויצירת קשר:
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לפייסבוק:   / matlabisrael  
ללינקדין:   / 1774805