💡 Get 7x PDF for 3D Data Tutorials here: [ Ссылка ]

The average LiDAR scan contains 250+ million points. Visualizing and sharing this data efficiently is a significant challenge for many professionals. This tutorial provides a no-code solution to visualize and manage massive point clouds early in the workflow.

Here are some of the topics I cover in this video:
✅ Command-line tools offer a powerful yet simple way to convert point cloud data.
✅ Software 1 is a versatile viewer for quick visualization and basic analysis.
✅ Software 2 creates web-ready point clouds for easy sharing and online exploration.
✅ Software 2 allows visualization of massive point clouds on your local machine.
✅ Combining these tools provides a comprehensive no-code workflow for handling large point clouds.

This video is an excellent resource for anyone who wants to learn how to build 3D data tools.

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WHO AM I?
If we haven’t yet before - Hey 👋 I’m Florent, a professor-turned-entrepreneur, and I’ve somehow become one of the most-followed 3D experts. Through my videos here on this channel and my writing, I share evidence-based strategies and tools to help you be better coders and 3D innovators.

📗 CHAPTERS
[00:00] Introduction: The Challenge of Big Point Clouds and Meshes
[00:30] Prerequisites: Command Line, CloudCompare, and Potree Desktop
[01:30] File Formats and Conversion using CloudCompare (Command Line)
[03:30] The Power of Octrees and Modified Nested Octrees
[05:30] Introducing Potree and PotreeConverter
[07:30] Drag-and-Drop Conversion and Visualization in Potree Desktop
[09:00] CloudCompare for Quick Views and Profiling
[11:00] Mesh Handling: Stanford Bunny Example
[13:00] Potree Desktop Features and Navigation
[15:00] Visualizing and Analyzing a Massive Point Cloud
[17:00] Exporting Profiles and Feature Computation in CloudCompare
[19:00] Conclusion and Next Steps

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