TCDM:基于变革复杂性的扭曲度量用于感知点云质量评估
IEEE transactions on visualization and computer graphics
|December 1, 2023
概括
本研究引入了一种通过测量转换复杂度来评估点云质量的新方法. 基于转换复杂性的扭曲度量 (TCDM) 在感知质量评估中取得了最先进的结果.
科学领域:
- 计算机视觉 计算机视觉
- 图像处理 图像处理
- 感知质量评估 感知质量评估
背景情况:
- 目标点云质量评估 (PCQA) 旨在获得感知上一致的定量指标.
- 现有的方法往往难以准确地捕捉人类视觉系统 (HVS) 的感知.
研究的目的:
- 为点云质量评估开发一种新的客观指标.
- 为了提高质量评估,利用认知科学和HVS直觉.
主要方法:
- 点云被细分为局部补丁使用3D沃罗诺伊图.
- 一个空间感知向量自回归 (SA-VAR) 模型编码参考和扭曲的补丁.
- 变换复杂性是使用协差矩阵和SA-VAR预测术语来计算的.
主要成果:
- 拟议的基于转变复杂性的扭曲度量 (TCDM) 在五个公共数据库上进行了评估.
- 在点云质量评估方面,TCDM取得了最先进的 (SOTA) 绩效.
- 该指标在各种实验场景中显示出强度.
结论:
- 通过量化转换复杂度,TCDM有效地衡量点云质量.
- 该方法为感知精确的客观PCQA提供了一个有希望的方向.
- 该方法显示了需要高保真度点云数据的现实应用程序的巨大潜力.
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