A Model Simplification Algorithm for Preserving Features Based on Quadratic Error Metrics
The edge-collapse simplification algorithm using quadratic error metrics provides a universal,efficient and high-quality model simplification solution.However,these methods still have some shortcomings,such as ignoring certain geometric features of the model,uniform model simplification,and difficulty in maintaining model shape char-acteristics at high simplification rates.Therefore,this paper proposes a model simplification algorithm based on quad-ratic error measurement,which incorporates vertex curvature,vertex planarity factor,and vertex surface area properties into the vertex quadratic error measurement,and changes the folding order of edges during the simplification process.The experimental results show that under the same simplification rate,this algorithm can achieve higher-quality model simplification and can maintain important geometric features of the model surface after large-scale simplification.
Model simplificationQuadric error metricEdge collapseGeometric features
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