A Point Cloud Simplification Algorithm Based on Weighted Feature Indexes for 3D Scanning Sensors.

ABSTRACT: Conventional point cloud simplification algorithms have problems including nonuniform simplification, a deficient reflection of point cloud characteristics, unreasonable weight distribution, and high computational complexity. A simplification algorithm, namely, the multi-index weighting simplification algorithm (MIWSA), is proposed in this paper. First, the point cloud is organized with a bounding box and kd-trees to find the neighborhood of each point, and the points are divided into small segments. Second, the feature index of each point is calculated to indicate the characteristics of the points. Third, the analytic hierarchy process (AHP) and criteria importance through intercriteria correlation (CRITIC) are applied to weight these indexes to determine whether each point is a feature p

SUBMITTER: Shi Z 

PROVIDER: S-EPMC9573161 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature