点云模型质量的客观评价是三维几何模型研究中不可或缺的工作. 根据显著性能够较好地反映人类视觉系统的特点，提出以点的法向量与其邻域点法向量的差异作为该点的显著性计算依据，利用原始点云模型和处理后点云模型在显著性上的差异判断点云模型质量的变化，实现点云模型的质量评价. 实验结果表明，所提出的客观评价模型和主观的人工评价得出的结果基本一致，且比信噪比方法更能体现人的视觉感知.
To deal with the huge amount of data in point cloud models, data must be compressed before use.Effective evaluation of quality degradation of the compressed point cloud model with respect to the original is needed. This work defines saliency of a cloud point that well reflects the human visual characteristics as the angular difference between the normal vector at the point and the average of normal vectors in its neighborhood. The difference in saliency between the compressed point cloud model and the original is taken as the objective quality index, which is easy to be calculated. Experiments on point cloud models with various resolutions indicate that the proposed method can give results conform to subjective evaluation.
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