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数学摄像头数组优化面部3D建模应用程序

Bashar Alsadik1, Luuk Spreeuwers2, Farzaneh Dadrass Javan1

  • 1Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, 7522 NB Enschede, The Netherlands.

Sensors (Basel, Switzerland)
|December 23, 2023
PubMed
概括
此摘要是机器生成的。

设计最佳的摄像机网络对于准确的3D面部建模至关重要. 七摄像头阵列配置为可靠的面部识别应用提供高精度,平衡精度和系统复杂性.

关键词:
3D模型是3D模型.摄像机网络 摄像机网络有约束的最小化最小化.面部识别系统是面部识别系统.优化的优化优化优化.摄影计量 (摄影计量) 是一种摄影仪.

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科学领域:

  • 计算机视觉 计算机视觉
  • 这是一种摄影计量技术 (photogrammetry).
  • 机器人技术 机器人技术 机器人技术

背景情况:

  • 摄像机网络设计复杂,影响3D面部建模等应用.
  • 由于硬件限制和低于最佳的系统配置,在3D面部模型中实现高精度是具有挑战性的.

研究的目的:

  • 为摄像机网络提供最佳的几何设计方法.
  • 调查多摄像头系统配置,以改进3D面部建模和识别.

主要方法:

  • 应用了一个数学非线性受约束优化技术.
  • 测试了四到八个摄像头的配置,用于面部3D模型质量评估.

主要成果:

  • 一个7摄像头阵列 (五角形有两个内部摄像头) 提供了高精度.
  • 一个9摄像头阵列提供高点密度.
  • 一个5摄像头阵列呈现了准确性和摄像头数量之间的平衡.

结论:

  • 七摄像头阵列是高精度3D面部建模的最佳选择.
  • 配置选择取决于优先考虑准确性,点密度或两者之间的平衡.