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Inspired by the advantages of the quadric error metrics initially shaped for mesh decimation, this study proposes an efficient mesh reconstruction method for 3D point clouds. This technique proceeds t...hrough clustering points enhanced with quadric error metrics, where each cluster gets a generator, an ideal 3D point for minimizing the total quadric error of the cluster. The approach places generators on prominent features and distributes errors evenly across clusters. It reconstructs the mesh using cluster adjacency and a constrained binary solver, while adaptively refining based on error. This approach investigates the effectiveness of Variational Shape Approximation via Quadric Error Metrics in handling point clouds and preserving the original shape of 3D models effectively. The proposed VSA-QEM integration aims to provide a more accurate and efficient simplification process, which is particularly beneficial for deployment on resource-constrained embedded systems.続きを見る
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Mendeley出力
2025_p0518