Cross-platform data fusion capabilities
Unlike traditional solutions that rely on a single data collection device, SpatialLM achieves unprecedented device compatibility:
- Support for sparse point clouds reconstructed from consumer-grade monocular camera video sequences
- Compatible with dense point clouds generated by RGBD cameras such as Microsoft Kinect
- Highly accurate laser point clouds acquired by vehicle/airborne LiDAR can be processed.
This multi-source data compatibility stems from an innovative point cloud normalization preprocessing technique, where all input data is passed through:
- Coordinate system standardization (Z-axis vertically upwards)
- Point density adaptive compensation
- Dynamic voxelization process (accuracy 0.05m)
In real-world tests, the model maintains more than 90% structural recognition consistency for different types of hybrid point cloud data.
This answer comes from the articleSpatialLM: Sweep the room, AI automatically draws 3D models for youThe
May not be reproduced without permission:AI productivity tools " SpatialLM has significant multi-source data compatibility advantages over traditional 3D scene analysis methods
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