Why point cloud 3D model is distorted in AI modeling?

Point cloud 3D models distort in AI modeling mainly due to noise, incomplete data coverage, or sensor calibration errors—these flaws make AI misinterpret spatial relationships, leading to warped shapes or wrong scales. - **Noise**: Fake points from sensors confuse AI, causing it to misconnect points. - **Incomplete data**: Gaps from occlusions (e.g., blocked objects) get filled inaccurately, distorting shapes. - **Calibration errors**: Mismatched sensor settings skew point positions, throwing off AI’s spatial understanding. To reduce distortion, first filter noise from the original point cloud or check for missing data—improving input quality usually fixes AI modeling errors.