An Improved Projector Calibration Method by Phase Mapping Based on Fringe Projection Profilometry by Yabin Liu, Bingwei Zhang, Xuewu Yuan, Junyi Lin, Kaiyong Jiang

“…One of the key ideas is to estimate the sub-pixel coordinates in the projector image plane using local random sample consensus (RANSAC). A bundle adjustment (BA) algorithm is adopted to optimize the calibration parameters to further improve the accuracy and robustness of the projector calibration. …”
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Model Based Automatic Segmentation Of Tree Stems From Single Scan Data by R. Boesch

“…Trees are cylinder shapes vertically located on a plane. Using a RANSAC-based segmentation approach, cylinders are fitted iteratively in the point cloud. …”
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Method for camera motion parameter estimation from a small number of corresponding points using quaternions by Ye.V. Goshin, A.P. Kotov

“…We propose method for determining motion parameters, including the selection of the most noise-free matches using the RANSAC method. The study presents results of an experiment on the “Middlebury” and “ETH3D” test kits, which contains a set of images with known values of the motion parameters. …”
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On-Site Sensor Recalibration of a Spinning Multi-Beam LiDAR System Using Automatically-Detected Planar Targets by Hsiang-Jen Chien, Chia-Yen Chen

“…We propose a temporal-spatial range data fusion algorithm, along with a robust RANSAC-based plane detection algorithm to address these issues. …”
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Mapping of Rubber Forest Growth Models Based on Point Cloud Data by Hang Zhou, Gan Zhang, Junxiong Zhang, Chunlong Zhang

“…Then, the structural parameters of the trunks calculated by RANSAC and IRTLS cylindrical fitting methods are compared separately. …”
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DM-SLAM: Monocular SLAM in Dynamic Environments by Xiaoyun Lu, Hu Wang, Shuming Tang, Huimin Huang, Chuang Li

“…Firstly, we proposed a distribution and local-based RANSAC (Random Sample Consensus) algorithm (DLRSAC) to extract static features from the dynamic scene based on awareness of the nature difference between motion and static, which is integrated into initialization of DM-SLAM. …”
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A Robust Linear Feature-Based Procedure for Automated Registration of Point Clouds by Martyna Poreba, François Goulette

“…The initial estimate is found from a triplet of conjugate line pairs, selected by a RANSAC algorithm. Then, this transformation is refined using an iterative optimization algorithm. …”
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PR-Alignment: Multidimensional Adaptive Registration Algorithm Based on Practical Application Scenarios by Wenxin Wang, Changming Zhao, Haiyang Zhang

“…By adding target scene classification information to the RANSAC algorithm, combined with geometric matching and photometric matching, we are able to complete the adaptive estimation of the transformation matrix. …”
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A Foot-Mounted Inertial Measurement Unit (IMU) Positioning Algorithm Based on Magnetic Constraint by Yan Wang, Xin Li, Jiaheng Zou

“…In the experiment, the features extracted by the multi-level Fourier transform method proposed in this paper are validated and the validity of loop closure matching is tested with a RANSAC-based method. Moreover, the loop closure detection results show that the cumulative error of the trajectory processed by the graph optimization algorithm is significantly suppressed, presenting a good accuracy. …”
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VOXEL-BASED POINT CLOUD LOCALIZATION FOR SMART SPACES MANAGEMENT by F. S. Mortazavi, O. Shkedova, U. Feuerhake, C. Brenner, M. Sester

“…The paper explains the registration and localization procedure of the point cloud dataset, which uses the KISS ICP for scan point cloud combination and the RANSAC method for the initial alignment of the combined point cloud. …”
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Transformation models for images by Cheah, Ann Chee

“…Using OpenCV library and two main algorithms, namely SIFT, a feature detector that extracts unique point of interest from an algorithm to find the descriptor of each of such key point and RANSAC, an iterative method to detect any outliers by estimating the parameters of the mathematical model from a set of observed data. …”
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Robust detection of degenerate configurations while estimating the fundamental matrix by Torr, PHS, Zisserman, A, Maybank, SJ

“…The method is called PLUNDER-DL and is a generalization of the robust estimator RANSAC.</p> <p>The method is evaluated on many differing pairs of real images. …”

Visual Localization and Target Perception Based on Panoptic Segmentation by Kefeng Lv, Yongsheng Zhang, Ying Yu, Zhenchao Zhang, Lei Li

“…Second, the semantic consistency score is introduced in the RANSAC process to estimate the optimal 6 degree-of-freedom (6DOF) pose. …”
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Adaptive feature extraction method for capsule endoscopy images by Dingchang Wu, Yinghui Wang, Haomiao Ma, Lingyu Ai, Jinlong Yang, Shaojie Zhang, Wei Li

“…Finally, a refined matching is obtained by applying the grid-based motion statistics algorithm to the result of Hamming distance, whereby mismatches are rejected using the RANSAC algorithm. Compared with the ASIFT method, which previously had the best performance, the average running time of AFFCEI was 4/5 that of ASIFT, and the average matching score improved by 5% when tracking features in a moving capsule endoscope.…”
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A 3D Scene Information Enhancement Method Applied in Augmented Reality by Bo Li, Xiangfeng Wang, Qiang Gao, Zhimei Song, Cunyu Zou, Siyuan Liu

“…In this paper, an optimized feature points extraction and matching algorithm based on Scale Invariant Feature Transform (SIFT) is proposed, and a fast spatial planes recognition method based on a RANdom SAmple Consensus (RANSAC) is established. Experiments show that the method can achieve higher accuracy compared to the Oriented Fast and Rotated Brief (ORB), Binary Robust Invariant Scalable Keypoints (BRISK) and Super Point. …”
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Research on Point Cloud Structure Detection of Manhole Cover Based on Structured Light Camera by Guijuan Lin, Hao Zhang, Siyi Xie, Jiesi Luo, Zihan Li, Yu Wang

“…Efforts have been dedicated to enhancing data quality by commencing with the acquisition and preprocessing of point cloud data from real-world manhole cover scenes. The RANSAC algorithm is subsequently employed to extract the road plane and determine the height of the point cloud structure. …”
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Robust pooling through the data mode by Ayman Mukhaimar, Ruwan Tennakoon, Reza Hoseinnezhad, Chow Yin Lai, Alireza Bab-Hadiashar

“…The proposed pooling layers look for data mode/cluster using two methods, RANSAC, and histogram, as clusters are indicative of models. …”
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A point cloud classification method for the Scan-to-BIM process in Architectural Heritage by Riccardo Tavolare, Elena Cabrera-Revuelta, Cesare Verdoscia, Michele Buldo

“…<br />In this scenario, the current work investigates the use of the CANUPO multiscale algorithm and the RANSAC model-fitting method for the classification of the staircase of Palazzo Nico, a neoclassical building in Gioia del Colle, Italy, using data obtained through TLS. …”
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An Accurate and Efficient Supervoxel Re-Segmentation Approach for Large-Scale Point Clouds Using Plane Constraints by Baokang Lai, Yingtao Yuan, Yueqiang Zhang, Biao Hu, Qifeng Yu

“…Additionally, supervoxels with roughness above a threshold are re-segmented using random sample consensus (RANSAC) to address multi-planar coupling within local areas of the point clouds. …”
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Pose Measurement Method Based on Machine Vision and Novel Directional Target by Dongri Shan, Zhihao Zhu, Xiaofang Wang, Peng Zhang

“…A planar target designed with circles and rings as the main body is dedicated to object pose measurement, and a feature point coordinate extraction and sorting algorithm is designed for this target to effectively extract image features on the target. The RANSAC algorithm and topology-based fitting for the intersection method are used to optimise data processing, further improving the accuracy of feature point coordinate extraction and ultimately achieving high-precision measurement of object poses. …”
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