Trifocal Tensor Based Feature Matching Algorithm

• 作者: Mingwei Shao Pan Wang
• 来源期刊: 北京理工大学学报（英文版）
• 学科: 工学
• 年，卷（期）: 2020,（4）
• 页码范围: 484-488
• 页数: 5页
• 分类号: TP751.1
• 语种: 英文
• DOI: 10.15918/j.jbit1004-0579.20039

摘要

Feature matching is of significance in the field of computer vision. In this paper, a trifoc-al tensor based feature matching algorithm is proposed for three views, including a trinocular vis-ion system. Initial matching point-pairs can be determined according to generic matching al-gorithms, on which an initial trifocal tensor of three views can be confirmed. Then the initial matching point-pairs should be re-selected. Meanwhile, the trifocal tensor will be recomputed. Iter-atively, the optimized trifocal tensor can be obtained. Compatible fundamental matrix of every two views can be determined. Furthermore, in the trinocular vision sensor, the trifocal tensor can be cal-culated based on the intrinsic parameter matrix of each camera. With the strict constraint provided by the trifocal tensor, feature matching results will be optimized. Experiments show that our pro-posed algorithm has the characteristics of feasibility and precision.