Online Inspection of 3D Parts via a Locally Overlapping Camera Network

被引:0
|
作者
Birdal, Tolga [1 ]
Bala, Emrah [2 ]
Eren, Tolga [2 ]
Ilic, Slobodan [3 ]
机构
[1] Tech Univ Munich, D-80290 Munich, Germany
[2] Gravi Ltd, Istanbul, Turkey
[3] Siemens AG, Munich, Germany
来源
2016 IEEE WINTER CONFERENCE ON APPLICATIONS OF COMPUTER VISION (WACV 2016) | 2016年
关键词
STEREO VISION;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The raising standards in manufacturing demands reliable and fast industrial quality control mechanisms. This paper proposes an accurate, yet easy to install multi-view, close range optical metrology system, which is suited to online operation. The system is composed of multiple static, locally overlapping cameras forming a network. Initially, these cameras are calibrated to obtain a global coordinate frame. During run-time, the measurements are performed via a novel geometry extraction techniques coupled with an elegant projective registration framework, where 3D to 2D fitting energies are minimized. Finally, a non-linear regression is carried out to compensate for the uncontrollable errors. We apply our pipeline to inspect various geometrical structures found on automobile parts. While presenting the implementation of an involved 3D metrology system, we also demonstrate that the resulting inspection is as accurate as 0.2 mm, repeatable and much faster, compared to the existing methods such as coordinate measurement machines (CMM) or ATOS.
引用
收藏
页数:10
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