🔷Point Cloud Normal Estimation

Functional Description

This operator is used to estimate surface normal vectors for each point in input point cloud data.

A normal vector is a three-dimensional vector perpendicular to the local surface where a point is located, representing the orientation of that point.

The operator uses a K-nearest neighbor based method: for each point in the point cloud, it finds its nearest K neighboring points, then fits a local plane through these neighboring points. The normal vector of this plane serves as the normal vector estimate for that point.

Usage Scenarios

  • Feature Extraction: Normal vectors and their distribution are important geometric features that can be used for point cloud matching, segmentation, and recognition tasks.

  • Plane Fitting and Detection: Normal vector information helps identify and segment planar regions.

  • Surface Analysis: Analyze object surface curvature, smoothness, etc.

  • Robot Grasping: When determining object surface graspability or calculating grasping poses, normal vector information may be needed.

Input Output

Input

Point Cloud: Input point cloud or point cloud list containing only XYZ coordinate information.

EstimateNormal input

Output

Point Cloud with Normals: Output point cloud or point cloud list that includes original XYZ coordinates plus estimated normal vector information for each point.

EstimateNormal output

Parameter Description

  • Computational Load: Normal estimation is computed point by point. More point clouds and larger K values result in longer computation time.

  • Viewpoint Importance: Must set correct viewpoint to ensure normal vector direction consistency.

Viewpoint

Parameter Description

Defines a three-dimensional coordinate [X, Y, Z], usually camera coordinate system origin [0, 0, 0], used to adjust computed normal vector directions.

Parameter Adjustment

Normal vectors have two possible directions (pointing inward or outward from surface). After computing initial normal vectors, the operator calculates the angle between the vector from current point to viewpoint and the initial normal vector. If the angle is greater than 90 degrees, the operator reverses the normal vector to ensure normal vectors roughly point toward the viewpoint direction.

Parameter Range

Default value: [0,0,0]

Search Count

Parameter Description

Number of neighboring points to find around each point when estimating normal vectors. These neighbors are used to fit a small plane, and the plane’s normal vector becomes that point’s normal vector.

Parameter Adjustment

Search count selection affects normal vector estimation stability and sensitivity to local details.

  • Fewer search count: More sensitive to local details, can better reflect normal changes in sharp edges or high curvature regions, but also more sensitive to noise, estimated normal vectors may be less smooth.

  • More search count: Considers larger neighborhood range, estimated normal vectors are smoother and insensitive to noise, but may smooth out some detail features, making normal transitions at edges less sharp.

Need to select appropriate search count based on point cloud density, noise level, and application requirements.

Parameter Range

[1, 200], Default value: 15

EstimateNormal k1

EstimateNormal k2

EstimateNormal k3

Search Count=5 (Detail Sensitive)

Search Count=15 (Default)

Search Count=200 (Highly Smooth)