“…The crucial part is the correspondence problem; finding the matching points of two images. The development of event-based cameras, inspired by the retina, enables the exploitation of an additional physical constraint—time. …”
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“…The feature point pair detecting method was designed based on Eigen-value of the feature windows gradient matrix, and the motion parameters equation was solved using the least square method and the matching point pairs got based on the optical flow. The condition number of coefficient matrix was proposed to quantificationally analyse the effect of matching errors on parameters solving errors. …”
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“…Finally, the simplified curves with the feature points are matched, and the similarities among the spectral curves are calculated using the matched points. The Airborne Visible Infrared Imaging Spectrometer (AVIRIS) and Reflective Optics System Imaging Spectrometer (ROSIS) hyperspectral image datasets are then selected to test the effect of the proposed index. …”
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“…The grid-based motion statistics (GMS) and RANSAC techniques are introduced to remove the outliers and preserve the correct matching points to deal with the mismatched pairs. Finally, the matching results for the rectified views are projected to the original viewpoint space, and the matches before and after distortion rectification are fused to further determine the final matches. …”
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“…Finally, the affine transformation matrix is calculated according to matched point pairs. Moreover, this paper presents an evaluation method to automatically estimate registration accuracy. …”
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“…The computing time can meet the requirements of real-time navigation, and the average running time of the KNN algorithm at each matching point is 5.87s. This algorithm shows better stability and anti-noise capability in the continuously matching process.…”
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“…The proposed technique converges to a matching point without the need of complex mathematical modelling of the system comprising of non-linear control elements. …”
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“…The occurrence of overlapping between the views of both cameras is predicted through geometrical modelling, activating a pseudo-stereo methodology which allows to instantly measure the depth by stochastic triangulation of matched points found through SIFT/SURF. Experimental validation is provided through results from experiments, where real data is captured as synchronized sequences of video and other data (relative pose of secondary camera) and processed off-line. …”
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“…The experimental results show that the proposed method can decrease the matching time and increase the number of matching points while maintaining high registration accuracy.…”
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“…The fundamental principle is to minimize the distances from the photogrammetric matching points to the terrestrial LiDAR data surface. …”
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“…For the other stage, to evaluate the similarity of the outputs, a pairwise similarity model is constructed by searching for the optimal matching points by setting temporal and spatial constraints. …”
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“…This verifies that the candidate image with the highest number of matching points is considered the best matching image.…”
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“…Two parental antibodies that each contain a single matched point mutation in the CH3 region were separately expressed in Chinese hamster ovary cells and manufactured at 1000 L scale using a platform fed-batch and purification process that was designed for standard antibody production. …”
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“…The matching process is based on the Speeded Up Robust Features (SURF) algorithm to find unique corresponding points between two DPRs (unknown person and database entry). The number of matching points found is an indicator for identification. …”
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“…Moreover, the stitching process is performed in two categories; manual point-to-point (mPTP) selection that performed by user specified corresponding matching points, and automated point-to-point (aPTP) selection that performed by SIFT algorithm. …”
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“…To address this issue, we incorporated single-matched point mutations in the CH3 domain to recapitulate the physiological process of human IgG4 Fab-arm exchange to generate monovalent bsAbs. …”
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“…The Szeliski grayscale fusion method directly calculates the grayscale average of the matching points to fuse the image, and finally, the best stitching method is used to eliminate the ghosting at the image mosaic. …”
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“…Because the traditional 3D registration model is prone to the problems of model position shift and inaccurate matching with the scene, the AKAZE-based tracking registration algorithm is improved, and a Multiple Filtering-AKAZE (MF-AKAZE) based on AKAZE is proposed to remove the matching points. The matching accuracy is increased by improving the RANSAC filtering mis-matching algorithm based on further screening of the matching results. …”
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“…A fundamental matrix estimation based on matching points is a critical problem in epipolar geometry. …”
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