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Volume 29Issue 4
Dec. 2020
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Mingwei Shao, Pan Wang. Trifocal Tensor Based Feature Matching Algorithm[J]. JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY, 2020, 29(4): 484-488. doi: 10.15918/j.jbit1004-0579.20039
Citation: Mingwei Shao, Pan Wang. Trifocal Tensor Based Feature Matching Algorithm[J].JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY, 2020, 29(4): 484-488.doi:10.15918/j.jbit1004-0579.20039
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Trifocal Tensor Based Feature Matching Algorithm

doi:10.15918/j.jbit1004-0579.20039

  • School of Information and Control Engineering, Qingdao University of Technology, Qingdao 266000, Shandong, China

Funds:the Key Research and Development Programs of Shandong Province(2018GGX101040); Applied Basic Research Programs of Qingdao(18-2-2-62-jch)
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    Abstract
  • Feature matching is of significance in the field of computer vision. In this paper, a trifocal tensor based feature matching algorithm is proposed for three views, including a trinocular vision system. Initial matching point-pairs can be determined according to generic matching algorithms, 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. Iteratively, 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 calculated 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 proposed algorithm has the characteristics of feasibility and precision.
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