没有合适的资源?快使用搜索试试~ 我知道了~
首页高精度与稳健的投影仪-相机标定方法
高精度与稳健的投影仪-相机标定方法
需积分: 13 4 下载量 55 浏览量
更新于2024-08-07
1
收藏 4.65MB PDF 举报
"Simple, Accurate, and Robust Projector-Camera Calibration.pdf" 本文主要探讨了简单、准确且鲁棒的投影仪-相机校准方法,这对于实现高精度的3D模型获取至关重要。在3D重建领域,结构光系统因其易用性和与昂贵激光扫描器相当的精度而受到青睐。这些系统通常由现成的数据投影仪和相机组成,但要达到高精度,必须对两者进行精确的校准。 传统的相机校准方法已经非常成熟,能够提供稳健的校准结果。然而,对于投影仪的校准,尽管相机和投影仪都可以用相同的数学模型来描述,但如何将这些方法有效地应用于投影仪仍然存在挑战。许多现有的投影仪校准技术倾向于采用简化的模型,忽视镜头畸变,这直接影响到校准的精度。 作者Daniel Moreno和Gabriel Taubin来自美国布朗大学工程学院,他们提出了一种新颖的方法来估计投影仪图像平面上3D点的图像坐标。这个方法依赖于一个未校准的相机,并利用局部单应性达到亚像素级别的精度。通过这种方法,可以避免因镜头畸变导致的精度损失,从而提高整个投影仪-相机系统的校准质量。 该研究中的技术不仅考虑了投影仪的特性,还兼顾了相机的校准,使得在实际应用中,即使面对复杂的环境和不完美的硬件,也能实现精确的3D信息捕捉。这一突破性的方法对于3D建模、机器人导航、增强现实以及任何依赖于精确投影和相机同步的领域都具有重要意义。 总结起来,这篇论文提供了投影仪-相机系统校准的新思路,通过亚像素级别的3D点坐标估计,提升了投影仪校准的精度,弥补了现有技术的不足,有望推动3D感知技术的进一步发展。
资源详情
资源推荐
Simple, Accurate, and Robust Projector-Camera Calibration
Daniel Moreno and Gabriel Taubin
School of Engineering
Brown University
Providence, RI, USA
Email: {daniel moreno,gabriel taubin}@brown.edu
Abstract—Structured-light systems are simple and effective
tools to acquire 3D models. Built with off-the-shelf components,
a data projector and a camera, they are easy to deploy and
compare in precision with expensive laser scanners. But such
a high precision is only possible if camera and projector are
both accurately calibrated. Robust calibration methods are well
established for cameras but, while cameras and projectors can
both be described with the same mathematical model, it is not
clear how to adapt these methods to projectors. In consequence,
many of the proposed projector calibration techniques make
use of a simplified model, neglecting lens distortion, resulting
in loss of precision. In this paper, we present a novel method
to estimate the image coordinates of 3D points in the projector
image plane. The method relies on an uncalibrated camera and
makes use of local homographies to reach sub-pixel precision.
As a result, any camera model can be used to describe the
projector, including the extended pinhole model with radial
and tangential distortion coefficients, or even those with more
complex lens distortion models.
Keywords-structured-light; camera; projector; calibration;
local homography;
I. INTRODUCTION
Structured-light systems are the preferred choice for do-it-
yourself 3D scanning applications. They are easy to deploy,
only an off-the-shelf data projector and camera are required,
and they are very accurate when implemented carefully. A
projector-camera pair works as a stereo system, with the
advantage that a properly chosen projected pattern simplifies
the task of finding point correspondences. In such systems,
projectors are modeled as inverse cameras and all consid-
erations known for passive stereo systems may be applied
with almost no change. However, the calibration procedure
must be adapted to the fact that projectors cannot directly
measure the pixel coordinates of 3D points projected onto
the projector image plane as cameras do.
Viewpoint, zoom, focus, and other parameters ought to be
adjusted, both in projector and camera, to match each target
object size and scanning distance; invalidating any previous
calibration. Therefore, structured-light systems must be cali-
brated before each use in order to guaranteed the best result,
turning the calibration procedure simplicity as valuable as
its precision. In this paper, we present a new calibration
procedure for structured-light systems that is both very easy
to perform and highly accurate.
Figure 1. Structured-light system calibration
The key idea of our method is to estimate the coordinates
of the calibration points in the projector image plane using
local homographies. First, a dense set of correspondences
between projector and camera pixels is found by projecting
onto the calibration object identical pattern sequence as the
one later projected to scan the target, reusing most of the
software components written for the scanning application.
Second, the set of correspondences is used to compute a
group of local homographies that allow to find the projection
of any of the points in the calibration object onto the
projector image plane with sub-pixel precision. In the end,
the data projector is calibrated as a normal camera.
Our main contribution is a method for finding correspon-
dences between projector pixels and 3D world points. Once
those correspondences are known any calibration technique
available for passive stereo can be applied directly to the
structured-light system. Our method does not rely on the
camera calibration parameters to find the set of correspon-
dences. As a result, the projector calibration is not affected
in any way by the accuracy of the camera calibration.
We show, as a second contribution, that the proposed
calibration method can be implemented in such a way that no
user intervention is necessary after data acquisition, making
the procedure effective even for unexperienced users. To
下载后可阅读完整内容,剩余7页未读,立即下载
仙猫漫步
- 粉丝: 22
- 资源: 37
上传资源 快速赚钱
- 我的内容管理 展开
- 我的资源 快来上传第一个资源
- 我的收益 登录查看自己的收益
- 我的积分 登录查看自己的积分
- 我的C币 登录后查看C币余额
- 我的收藏
- 我的下载
- 下载帮助
最新资源
- 最优条件下三次B样条小波边缘检测算子研究
- 深入解析:wav文件格式结构
- JIRA系统配置指南:代理与SSL设置
- 入门必备:电阻电容识别全解析
- U盘制作启动盘:详细教程解决无光驱装系统难题
- Eclipse快捷键大全:提升开发效率的必备秘籍
- C++ Primer Plus中文版:深入学习C++编程必备
- Eclipse常用快捷键汇总与操作指南
- JavaScript作用域解析与面向对象基础
- 软通动力Java笔试题解析
- 自定义标签配置与使用指南
- Android Intent深度解析:组件通信与广播机制
- 增强MyEclipse代码提示功能设置教程
- x86下VMware环境中Openwrt编译与LuCI集成指南
- S3C2440A嵌入式终端电源管理系统设计探讨
- Intel DTCP-IP技术在数字家庭中的内容保护
资源上传下载、课程学习等过程中有任何疑问或建议,欢迎提出宝贵意见哦~我们会及时处理!
点击此处反馈
安全验证
文档复制为VIP权益,开通VIP直接复制
信息提交成功