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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

概括

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.

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.

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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