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Journal articles on the topic 'Epipolar constraint'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

Xu, Yang, Jun Peng, Wentao Yu, Yuan Fang, and Weirong Liu. "Three-Step Epipolar-Based Visual Servoing for Nonholonomic Robot with FOV Constraint." Journal of Applied Mathematics 2014 (2014): 1–14. http://dx.doi.org/10.1155/2014/638539.

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Image-based visual servoing for nonholonomic mobile robots using epipolar geometry is an efficient technology for visual servoing problem. An improved visual servoing strategy, namely, three-step epipolar-based visual servoing, is developed for the nonholonomic robot in this paper. The proposed strategy can keep the robot meeting FOV constraint without any 3D reconstruction. Moreover, the trajectory planned by this strategy is shorter than the existing strategies. The mobile robot can reach the desired configuration with exponential converge. The control scheme in this paper is divided into three steps. Firstly, by using the difference of epipoles as feedback, the robot rotates to make the current configuration and desired configuration in the same orientation. Then, by using a linear input-output feedback, the epipoles are zeroed so as to align the robot with the goal. Finally, by using the difference of feature points, the robot reaches the desired configuration. Simulation results and experimental results are given to illustrate the effectiveness of the proposed control scheme.

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He, Qing, Ning Wei, Wei Liu, Chao Hu, and Q. H. Meng. "Enhanced Epipolar Constraint for Point Correspondence in Computer Vision System." Applied Mechanics and Materials 58-60 (June 2011): 1871–76. http://dx.doi.org/10.4028/www.scientific.net/amm.58-60.1871.

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Some projective points (2D-points) of the same 3D-point captured by different cameras are called corresponding points. The task of finding the corresponding points is named as point correspondence. It is a essential problem in computer vision, and it paves the way for 3D reconstruction. Epipolar constraint is a widely-used geometric constraint for point correspondence, some methods based on it have been proposed for this task. However, the threshold is set by empirical approach in these methods; this approach is influenced by the parameters of cameras. On the other hand, epipolar constraint is not a sufficient condition for this task; this will result in the mismatch for two 2D-points. According to the rule of Propagation Uncertainty and practical situation of the computer vision system, this paper introduces the enhanced epipolar constraint comprising normalized coplanar constraint, nonparallel constraint and interval constraint. The normalized coplanar constraint provides a simple and rational method to set the threshold of epipolar constraint; the nonparallel constraint and interval constraint can reduce the occasion of mismatch.

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Wei, Ning, Chao Hu, Qing He, Wei Liu, and Q. H. Meng. "Angle Constraints for Point Correspondence in Multi-Ocular Vision." Applied Mechanics and Materials 58-60 (June 2011): 1384–89. http://dx.doi.org/10.4028/www.scientific.net/amm.58-60.1384.

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Geometric constraints have an essential significance for point correspondence in computer vision systems. Traditional epipolar constraint in bi-ocular system faces two main problems: threshold-setting and corresponding ambiguities. This paper describes a collinear epipolar plane model and proposes a novel criterion for bi-ocular corresponding which allows setting a uniform threshold. Furthermore, it proposes the concept tri-correspondence units, proves their specificity against ambiguities, and discusses the merging of them.

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Hosseinyalamdary, S., and A. Yilmaz. "Motion Vector Field Estimation Using Brightness Constancy Assumption and Epipolar Geometry Constraint." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences II-1 (November 7, 2014): 9–16. http://dx.doi.org/10.5194/isprsannals-ii-1-9-2014.

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In most Photogrammetry and computer vision tasks, finding the corresponding points among images is required. Among many, the Lucas-Kanade optical flow estimation has been employed for tracking interest points as well as motion vector field estimation. This paper uses the IMU measurements to reconstruct the epipolar geometry and it integrates the epipolar geometry constraint with the brightness constancy assumption in the Lucas-Kanade method. The proposed method has been tested using the KITTI dataset. The results show the improvement in motion vector field estimation in comparison to the Lucas-Kanade optical flow estimation. The same approach has been used in the KLT tracker and it has been shown that using epipolar geometry constraint can improve the KLT tracker. It is recommended that the epipolar geometry constraint is used in advanced variational optical flow estimation methods.

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Sun, Xue Qi, Ming Li Dong, and Jun Wang. "Matching Algorithm of Binocular Dynamic Vision Measurement." Applied Mechanics and Materials 278-280 (January 2013): 764–70. http://dx.doi.org/10.4028/www.scientific.net/amm.278-280.764.

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In order to realize the correspondence of feature points in the binocular dynamic vision measurement system, the two homologous images matching problem in the paper is studied. First of all, a method of strong space resection. The strong space resection optimizes the elements of exterior orientation, improves the precision, so as to improve the calculating precision of epipolar line. Secondly, an algorithm of multiple restriction matching which is for two homologous images matching of feature points has been introduced. This algorithm based on epipolar line constrain, increases the uniqueness constraint and double constraint, combined with the second match with disparity gradient constrain, finally get the correct matching relationship of feature points in two homologous images. The experimental results show that: this method for matching of binocular dynamic vision measurement system, can get 100% of the matching accuracy rate. And it would satisfy the need of binocular dynamic vision measurement system.

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Zhang, Ke, and Zhao Gao. "The Technology of Fast 3D Reconstruction Based on Stereo Vision." Key Engineering Materials 579-580 (September 2013): 654–58. http://dx.doi.org/10.4028/www.scientific.net/kem.579-580.654.

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Reverse engineering has become an independent research area in CAD/CAM system with the development of modern manufacturing. The 3D reconstruction technology of generating a digit model from physical model is an important part of reverse engineering. The 3D reconstruction technology based on stereo vision has advantages such as non-contact measurement, simple system structure, being fast and efficient. In this paper, a fast 3D reconstruction technology based on stereo vision is presented. Firstly, BP neural network is used to simulate the mapping relationship between the 3D object and its images. Then, the epipole positions and adjusting coefficients for epipolar lines are calculated according to the epipolar line constraint. After the rectification transformations on the left and right image planes is conducted, the pairs of conjugate epipolar lines become collinear and parallel to the horizontal image axis. Therefore, when the stereo correspondences between the left and right images are being performed, the search is done only along the horizontal lines of the rectified images, which is highly advantageous to fast image matching for stereo vision and 3D reconstruction of free-form surface.

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7

Gong, D., Y. Han, and L. Zhang. "QUANTITATIVE ASSESSMENT OF THE PROJECTION TRAJECTORY-BASED EPIPOLARITY MODEL AND EPIPOLAR IMAGE RESAMPLING FOR LINEAR-ARRAY SATELLITE IMAGES." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences V-1-2020 (August 3, 2020): 89–94. http://dx.doi.org/10.5194/isprs-annals-v-1-2020-89-2020.

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Abstract. Epipolar geometry rectification is one of the critical issues in photogrammetry, which is a strong corresponding searching constraint in dense image matching for 3D reconstruction. In this paper, the properties of the projection trajectory-based epipolarity model are analyzed quantitatively, and the approximate straight line and parallelism property of the epipolar curve are discussed comprehensively using the linear pushbroom satellite images, i.e. IKONOS, GeoEye images. Based on the analysis of the epipolar line properties, a practical method for epipolar resampling developed. In this method, the pixelwise relationship is established between the original and the epipolar images. The experiments on TH-1 images show that quasi rigorous epipolar images can be resampled using our proposed method for both along-track images. After epipolar geometry rectification, the vertical parallaxes at checkpoints can achieve sub-pixel level accuracy, thus demonstrating the correctness and applicability of the proposed method.

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Zhang, Qian Qian, Ming Li Dong, Peng Sun, and Jun Wang. "Automatic Matching Based on Dynamic Threshold in Close-Range Photogrammetry." Advanced Materials Research 418-420 (December 2011): 1973–79. http://dx.doi.org/10.4028/www.scientific.net/amr.418-420.1973.

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Points matching is a key technology in close-range photogrammetry. The epipolar line constraint that confines the research area from two dimensions to one dimension, can improve the efficiency of matching process. In the paper, coded targets are applied to get a set of accurate correspondences of points between images, and then the correspondence set is used for calculating fundamental matrices by normalized 8-points algorithm that can be implemented quickly and simply. Because of the ambiguities, a completely accurate correspondence set will not be gained only by epipolar line constraint, and other technologies should be combined with epipolar line constraint. Three views are used to decrease ambiguities, and a method of dynamic threshold is presented to reject wrong correspondences. A proper threshold is calculated, and those correspondences whose corresponding distance is larger than the dynamic threshold, are considered as wrong matching points. Many experiments show that the correct rate of matching is about 99.98%, which means an automatic, efficient, accurate matching process can be implemented by the methods in this paper.

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9

Lehtola, Ville, Matti Kurkela, and Petri Rönnholm. "Radial Distortion from Epipolar Constraint for Rectilinear Cameras." Journal of Imaging 3, no. 1 (January 24, 2017): 8. http://dx.doi.org/10.3390/jimaging3010008.

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10

Liu, Xiaochen, and Suping Fang. "Correcting large lens radial distortion using epipolar constraint." Applied Optics 53, no. 31 (October 27, 2014): 7355. http://dx.doi.org/10.1364/ao.53.007355.

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11

Li, He Xi, and J. J. Zhang. "3-D Measurement and Reconstruction of Workpieces in Robotic Stereovision System." Applied Mechanics and Materials 743 (March 2015): 783–86. http://dx.doi.org/10.4028/www.scientific.net/amm.743.783.

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An epipolar line constraint equation for robotic binocolar stereovision (BSV) is first established for the measurement and reconstruction of workpiece surface, in which the intrinsic parameters of two cameras and their extrinsic structural parameters with respect to a robotic reference base are included. To determine a sole matching point between left and right images, a laser emmiter is added to BSV to form a stripe on workpiece surface, experimental results show that the measurement accuracy of 3-dimensional (3-D) workpiece surface can be improved by combining epipolar line constraint with laser stripe projection, and the 3-D workpiece surface can be reconstructed with less errors.

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12

Lim, J., N. Barnes, and Hongdong Li. "Estimating Relative Camera Motion from the Antipodal-Epipolar Constraint." IEEE Transactions on Pattern Analysis and Machine Intelligence 32, no. 10 (October 2010): 1907–14. http://dx.doi.org/10.1109/tpami.2010.113.

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13

Zhang Qingzhe, 张青哲, and 王勇 Wang Yong. "Binocular Stereo Vision Calibration Accuracy Evaluation Using Epipolar Constraint." Laser & Optoelectronics Progress 56, no. 23 (2019): 231504. http://dx.doi.org/10.3788/lop56.231504.

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Wang, Chuan, Jie Yang, and Yan Wei Zhou. "The Technology of Circular Parts Precise Measurement Based on Binocular Calibration." Applied Mechanics and Materials 333-335 (July 2013): 199–206. http://dx.doi.org/10.4028/www.scientific.net/amm.333-335.199.

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A method of measuring the radius of circular parts by binocular stereo vision technology is proposed. First of all the interior and exterior parameters of cameras are acquired by the camera calibration technology. Then the epipolar constraint can be calculated which contains the calibrated information. The image matching which uses the epipolar constraint is done to find the matching points. The three dimensional (3D) coordinates of edges points are reconstructed through trigonometry reconstruction. At last the analytic expression of the plane in which the circle lies and the circles radius are calculated in two steps by Levenberg-Marquardt (LM) algorithm. The proposed method does not require the prior knowledge of position between the measuring plane and the calibration plane which monocular measurement needs. Experimental results show that the measurement has high precision.

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15

Schneider, J., C. Stachniss, and W. Förstner. "ON THE QUALITY AND EFFICIENCY OF APPROXIMATE SOLUTIONS TO BUNDLE ADJUSTMENT WITH EPIPOLAR AND TRIFOCAL CONSTRAINTS." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences IV-2/W3 (August 18, 2017): 81–88. http://dx.doi.org/10.5194/isprs-annals-iv-2-w3-81-2017.

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Bundle adjustment is a central part of most visual SLAM and Structure from Motion systems and thus a relevant component of UAVs equipped with cameras. This paper makes two contributions to bundle adjustment. First, we present a novel approach which exploits trifocal constraints, i.e., constraints resulting from corresponding points observed in three camera images, which allows to estimate the camera pose parameters without 3D point estimation. Second, we analyze the quality loss compared to the optimal bundle adjustment solution when applying different types of approximations to the constrained optimization problem to increase efficiency. We implemented and thoroughly evaluated our approach using a UAV performing mapping tasks in outdoor environments. Our results indicate that the complexity of the constraint bundle adjustment can be decreased without loosing too much accuracy.

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Tian, Jindong, Yabin Ding, and Xiang Peng. "Self-calibration of a fringe projection system using epipolar constraint." Optics & Laser Technology 40, no. 3 (April 2008): 538–44. http://dx.doi.org/10.1016/j.optlastec.2007.08.009.

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Chai, Xinghua, Fuqiang Zhou, and Xin Chen. "Epipolar constraint of single-camera mirror binocular stereo vision systems." Optical Engineering 56, no. 08 (August 19, 2017): 1. http://dx.doi.org/10.1117/1.oe.56.8.084103.

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18

Ma, Y., R. Vidal, S. Hsu, and S. Sastry. "Optimal motion estimation from multiple images by normalized epipolar constraint." Communications in Information and Systems 1, no. 1 (2001): 51–74. http://dx.doi.org/10.4310/cis.2001.v1.n1.a4.

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Xu, Shuo Bo, Di Shi Xu, and Hua Fang. "Stereo Matching Algorithm Based on Detecting Feature Points." Advanced Materials Research 433-440 (January 2012): 6190–94. http://dx.doi.org/10.4028/www.scientific.net/amr.433-440.6190.

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A new method for solving the stereo matching problem in the presence of large occlusion is presented. This method for stereo matching and occlusion detection is based on searching disparity point. In this paper, we suppose that a pair of epipolar-line images is a projection of a group of piece-wise straight lines on the left and right images respective. Therefore the disparity curve corresponding to a pair of epipolar-line images may be approximated by a group of piece-wise straight lines. Then the key of solving disparity curve is how to get the “characteristic points” on the group of piece-wise straight lines. Based on this view, we fetched out the conception “disparity point”, and three kinds of special disparity points are correctly corresponding to the “characteristic point”. By analyzing intensity property of a disparity point and its neighbor points, an approach which combines stepwise hypothesis-verification strategy with three constraint conditions is devised to extract the candidate disparity points from the epipolar images.

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20

Chen, Lin, Rong Sheng Lu, Yan Qiong Shi, and Jian Sheng Tian. "A Differential Evolution Stereo Matching Method in Digital Image Correlation." Key Engineering Materials 625 (August 2014): 297–304. http://dx.doi.org/10.4028/www.scientific.net/kem.625.297.

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Stereo matching is widely used in three-dimensional (3D) reconstruction, stereo machine vision and digital image correlation. The aim of stereo matching process is to solve the well-known correspondence problem, which tries to match points or features from one image with the same points or features in another image from the same 3D scene. There are two basic ways, correlation-based and feature-based, are used to find the correspondences between two images. The correlation-based way is to determine if one location in one image looks/seems like another in another image, and the feature-based way to find if a subset of features in one image is similar in the another image. In stereo matching, a simple algorithm is to compare small patches between two rectified images by correlation search. For the pair images acquired from two cameras inevitably exists some rotation transformation, the algorithm first runs a preprocessing step to rectify the images with the epipolar rectification to simplify the problem of finding matching points between images. The epipolar rectification is to determine a transformation of each image plane such that pairs of conjugate epipolar lines become collinear and parallel to one of the image axes. It will lead the loss of gray information of images. The effect is dependent on the amount of angle. When the angle is big enough, the correlation search may yield error results because of retrograded correlation effect. In order to solve the problem, the paper presents an improved stereo matching algorithm with differential evolution to solve the correspondence problem. Our method doesn’t need to runs the preprocessing step to rectify the images with the epipolar rectification. It uses a differential evolution algorithm to minimize the correlation function which contains the angle information after acquiring the epipoar geometry constraint of two image pairs. Then it utilizes a flood-fill algorithm to search correspondence sub-region in the area around the epipolar line. The flood-fill algorithm can overcome the problem of the traditional row-column scanning search method, which will encounter boundary barrier where exists concave polygons or cavities. The Experimental results show that the proposed method can be easily implemented in stereo matching without loss of information of image features with large rotation angle transformation. In the paper, we will introduce the stereo matching principle and its algorithms, including the differential evolution algorithm for finding the correspondences with large rotation transformation between stereo image pairs and the flood-fill traversal strategy for matching large area with complex concave polygons or cavities. In the end of the paper, some experimental results will be given to illustrate the method effectiveness. Keywords: digital image correlation, stereo matching algorithm, epipolar geometry, flood fill algorithm, differential evolution, rotation angle

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CHEN Yi-chao, 陈一超, 刘秉琦 LIU Bing-qi, and 黄富瑜 HUANG Fu-yu. "Ultra-wide Field Infrared Binocular Vision Epipolar Constraint and Spatial Positioning." ACTA PHOTONICA SINICA 48, no. 2 (2019): 211003. http://dx.doi.org/10.3788/gzxb20194802.0211003.

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Pritt, Mark D. "Image registration with use of the epipolar constraint for parallel projections." Journal of the Optical Society of America A 10, no. 10 (October 1, 1993): 2187. http://dx.doi.org/10.1364/josaa.10.002187.

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Da Jian, 笪健, 屈惠明 Qu Huiming, 陶天阳 Tao Tianyang, 陈钱 Chen Qian, and 左超 Zuo Chao. "Real-Time Three-Dimensional Measurement Composite of Epipolar Constraint and Speckle Correlation." Acta Optica Sinica 36, no. 10 (2016): 1012003. http://dx.doi.org/10.3788/aos201636.1012003.

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Qi, Zhaoshuai, Zhao Wang, Junhui Huang, Chao Xing, and Jianmin Gao. "Invalid-point removal based on epipolar constraint in the structured-light method." Optics and Lasers in Engineering 105 (June 2018): 173–81. http://dx.doi.org/10.1016/j.optlaseng.2018.01.018.

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Xu, Zhengwei, Chengke Wu, Chenjing Pang, and Peiyi Shen. "A 3-D reconstruction method based on the constraint of epipolar geometry." Journal of Electronics (China) 15, no. 3 (July 1998): 274–77. http://dx.doi.org/10.1007/s11767-998-0040-9.

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Xu, Fuyuan, Guohua Gu, Kan Ren, and Weixian Qian. "Motion Segmentation by New Three-View Constraint from a Moving Camera." Mathematical Problems in Engineering 2015 (2015): 1–14. http://dx.doi.org/10.1155/2015/546580.

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We propose a new method for the motion segmentation using a moving camera. The proposed method classifies each image pixel in the image sequence as the background or the motion regions by applying a novel three-view constraint called the “parallax-based multiplanar constraint.” This new three-view constraint, being the main contribution of this paper, is derived from the relative projective structure of two points in three different views and implemented within the “Plane + Parallax” framework. The parallax-based multiplanar constraint overcomes the problem of the previous geometry constraint and does not require the reference plane to be constant across multiple views. Unlike the epipolar constraint, the parallax-based multiplanar constraint modifies the surface degradation to the line degradation to detect the motion objects followed by a moving camera in the same direction. We evaluate the proposed method with several video sequences to demonstrate the effectiveness and robustness of the parallax-based multiplanar constraint.

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Asl, Habib Ghanbarpour, and Abbas Dehghani Firouzabadi. "Integration of the inertial navigation system with consecutive images of a camera by relative position and attitude updating." Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering 233, no. 15 (May 31, 2019): 5592–605. http://dx.doi.org/10.1177/0954410019852818.

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This paper introduces a new method for improving the inertial navigation system errors using information provided by the camera. An unscented Kalman filter is used for integrating the inertial measurement unit data with the features’ constraints extracted from the camera’s image. The constraints, in our approach, comprise epipolar geometry of two consecutive images with more than 65% coverage. Tracking down a known feature in two consecutive images results in emergence of stochastic epipolar constraint. It emerges in the form of an implicit measurement equation of the Kalman filter. Correctly matching features of the two images is necessary for reducing the navigation system errors because they act as external information for the inertial navigation system. A new method has been presented in this study based on the covariance analysis of the matched feature rays’ intersection points on the ground, which sieves the false matched features. Then, the inertial navigation system and matched feature information is integrated through the unscented Kalman filter filter and the states of the vehicle (attitude, position, and velocity) are corrected according to the last image. In this paper, the relative navigation parameters against the absolute one have been corrected. To avoid increasing dimensions of the covariance matrix, sequential updating procedure is used in the measurement equation. The simulation results show good performance of the proposed algorithm, which can be easily utilized for real flights.

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Zheng, Shun Yi, Hua Liang Hu, Xuan Xu, and Kai Le. "Structured-Light-Based 3D Reconstruction Using Gray Code and Line-Shift Stripes." Advanced Materials Research 108-111 (May 2010): 799–804. http://dx.doi.org/10.4028/www.scientific.net/amr.108-111.799.

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The structured light can be used to extract the 3D information through obtaining the three-dimensional points from being measured object, and this method is simple, fast and accurate. However, the key factor of this process is how to inspect the stripes accurately. To improve the accuracy, in this paper, we firstly locate the stripes of the structured light roughly by use of the gray code images, and then locate it accurately by utilizing the line-shift stripes code images. Finally we turn the two dimensions search into one dimension search in the image match by using of epipolar constraint, and the intersection points of the stripes of structured light and the epipolar line are final match points. Finally, space intersection has been used to obtain three-dimensional points. Repeated experiments prove that wonderful effect can be obtained by this method.

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Limei, SONG, LYU Kunkun, and YANG Yan’gang. "3-D human pose measurement method based on deep learning and epipolar constraint." Journal of Applied Optics 41, no. 6 (2020): 1166–73. http://dx.doi.org/10.5768/jao202041.0601005.

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Shan Baohua, 哈尔滨工业大学土木工程学院, 黑龙江哈尔滨, 哈尔滨工业大学结构工程灾变与控制教育部重点实验室, 黑龙江哈尔滨, 哈尔滨工业大学土木工程智能防灾减灾工业与信息化部重点实验室, and 黑龙江哈尔滨. "A Stereovision Measurement Method Using Epipolar Constraint to Correct Digital Image Correlation Matching." Chinese Journal of Lasers 44, no. 8 (2017): 0804003. http://dx.doi.org/10.3788/cjl201744.0804003.

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Guan, Banglei, Yingjian Yu, Ang Su, Yang Shang, and Qifeng Yu. "Self-calibration approach to stereo cameras with radial distortion based on epipolar constraint." Applied Optics 58, no. 31 (October 29, 2019): 8511. http://dx.doi.org/10.1364/ao.58.008511.

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Balcaen, R., P. L. Reu, and D. Debruyne. "Stereo-DIC Uncertainty Estimation Using the Epipolar Constraint and Optimized Three Camera Triangulation." Experimental Techniques 42, no. 1 (November 2, 2017): 115–20. http://dx.doi.org/10.1007/s40799-017-0207-0.

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ZUO, AIQIU, JASON Z. ZHANG, KEVIN STANLEY, and Q. M. JONATHAN WU. "A HYBRID STEREO FEATURE MATCHING ALGORITHM FOR STEREO VISION-BASED BIN PICKING." International Journal of Pattern Recognition and Artificial Intelligence 18, no. 08 (December 2004): 1407–22. http://dx.doi.org/10.1142/s0218001404003794.

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Stereo vision-based bin picking systems require accurate 3D information to be recovered from 2D stereo images. To achieve this goal, we have developed a hybrid coarse-to-fine algorithm for stereo feature matching, which is based on the 2D six-parameter affine transformation and local similarity evaluation. With this algorithm, the coarse matching is performed by the 2D six-parameter affine transformation to get rough feature matches, imposing a strong constraint to further search instead of the traditional epipolar constraint. To obtain precise matches, the perspective effect is dealt with fine stereo feature matching by performing local similarity evaluation on the attribute vectors of features. Experimental results proving the performance of the stereo feature matching algorithm are also presented.

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Gao, Qing Ji, and Lu Yang. "Baggage Specification Detection Based on the Binocular Vision." Applied Mechanics and Materials 278-280 (January 2013): 861–65. http://dx.doi.org/10.4028/www.scientific.net/amm.278-280.861.

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To the baggage specification automatically detection problem of self-service bag drop system, a baggage size detection algorithm based on stereo vision is proposed. The algorithm is based on binocular stereo vision measurement principle. Firstly, the canny edges of baggage image are extracted as the feature points. With the disparity gradient constraint and epipolar constraint, Stereo matching algorithm based on edge features is proposed, meanwhile, the two images play a symmetric role to ensure the reliability of matching in the matching process. The coordinates of the three dimensional points are derived with approximation of the middle point of the common perpendicular line in different planes. Experimental results show that the proposed algorithm can detect the baggage specification with appropriate accuracy.

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Shan, Baohua, Yunfeng Pan, Xiaoyang Huo, and Guijun Xian. "Detection of slip for CFRP-concrete interface using stereovision method corrected by epipolar constraint." Structural Control and Health Monitoring 25, no. 10 (July 13, 2018): e2212. http://dx.doi.org/10.1002/stc.2212.

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Ankamuthu, Sathish, Ram Balachandar, and Hugh Wood. "Computational stereoscopy for three-dimensional scour depth measurement in channels." Canadian Journal of Civil Engineering 26, no. 6 (December 1, 1999): 698–712. http://dx.doi.org/10.1139/l99-032.

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Local channel scour is a problem of substantial importance in hydraulic engineering practice. Scour occurring around hydraulic structures has serious consequences in terms of damage to the structure and to human safety. The mechanisms of scour are complex and dynamic. This has resulted in most of the studies dealing with local scour to be experimental in nature. The amount of erosion has generally been quantified by noting the depth of scour at various locations in the bed. When the flow is unsteady or quasi-steady, determining the instantaneous depth is not a trivial task and involves a three-dimensional analysis of the scour field. Furthermore, the depth measurement has to be non-intrusive. The present study aims at developing a practical video image analysis for use in three-dimensional scour depth measurement. To acquire images, two cameras with similar specifications were mounted over the model of the eroded bed and the two images were simultaneously captured to simulate stereoscopic viewing. The computational scheme involved the use of an epipolar constraint and a relaxation technique to match corresponding points in the pair of stereo images. A correlation technique was developed to eliminate false matches. The depth of scour was determined using the parallax between the matched points. Following the successful application of the stereoscopy procedure to grayscale images, the scheme was applied to colour images using the pixel hue, saturation, and intensity values.Key words: stereoscopy, scour, epipolar constraint, relaxation technique, correlation technique.

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Li, Jia Lu, Lin Bing Long, and Bao Feng Zhang. "Localization of Mobile Robot Based on Least Square Method." Applied Mechanics and Materials 347-350 (August 2013): 808–11. http://dx.doi.org/10.4028/www.scientific.net/amm.347-350.808.

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Localization is the basis for navigation of mobile robots. This paper focuses on key techniques of localization for mobile robots based on vision. Firstly, the specific measures and steps of the algorithm are analyzed and researched in depth. In the study, SIFT algorithm combined with epipolar geometry constraint is used on the environment feature point detection, matching and tracking. And the method of RANSAC combined with the least squares is used to obtain accurate results of the motion estimation. Then the necessary experiments are carried out to verify the correctness and effectiveness of algorithms. The experimental results verified the accuracy of the improved algorithm.

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Cang, Yan, Hengxiang He, and Yulong Qiao. "Measuring the Wave Height Based on Binocular Cameras." Sensors 19, no. 6 (March 17, 2019): 1338. http://dx.doi.org/10.3390/s19061338.

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The wave is an important hydrological element in marine research. Accurately describing the characteristics of waves is therefore significant to the study of marine power. The contents of this article are as follows: (1) a wave height measurement system using binocular cameras is proposed, and the small tank experiments are conducted to prove the efficacy of the proposed system; (2) based on the scale invariant feature transition (SIFT) algorithm, sub-pixel Harris corners are calculated in the difference-of-Gaussian (DOG) space to locate key points more accurately; and (3) a bi-directional epipolar constraint is employed to decrease the mismatch rate and computation time.

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Guo, Yu Bo, Gang Chen, Dong Ye, and Feng Yuan. "Camera Calibration of Binocular Vision Based on Virtual 1D Target." Advanced Materials Research 605-607 (December 2012): 859–63. http://dx.doi.org/10.4028/www.scientific.net/amr.605-607.859.

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A field calibration method based on virtual 1D target is proposed for the extrinsic parameters of binocular vision. A target is placed on high precision 1D lifting platform to create virtual 1D target through motions of lifting platform. Two cameras are used to obtain virtual target images of different positions and preliminarily achieve extrinsic parameter calibration of binocular vision based on epipolar constraint equation. Finally, the length of virtual 1-D target is used to optimize the extrinsic parameters. This method is featured with easy operation, flexible application and field calibration. The experimental results verify the feasibility of this calibration method and show it can yield high field calibration precision.

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Fan, Shengli, Mei Yu, Gangyi Jiang, Yigang Wang, Hao Jiang, and Qingbo Zhang. "A Mismatch Detection Method Based on Affine Transformation for Stereo Light Microscopy Stereo Matching." International Journal of Pattern Recognition and Artificial Intelligence 31, no. 05 (February 27, 2017): 1750013. http://dx.doi.org/10.1142/s0218001417500136.

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For the light microscopy images that have the characteristics of shallow depth of field, serious distortion and poor resolution, mismatch is a ubiquitous phenomenon. The paper presents a mismatch detection method for the stereo light microscopy stereo matching. Affine transformation matrix and matching constraint condition are calibrated by the calibration board which has the precision solid dots and the motorized stage. Bias vector of affine transformation of each matching pair is taken as the criteria to apply mismatch detection. The experimental results show that the method can detect more mismatching pairs and preserve more matching pairs than the traditional RANSAC method and the epipolar rectification method.

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Wang, Huai-Mu, Huei-Yung Lin, and Chin-Chen Chang. "Object Detection and Depth Estimation Approach Based on Deep Convolutional Neural Networks." Sensors 21, no. 14 (July 12, 2021): 4755. http://dx.doi.org/10.3390/s21144755.

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In this paper, we present a real-time object detection and depth estimation approach based on deep convolutional neural networks (CNNs). We improve object detection through the incorporation of transfer connection blocks (TCBs), in particular, to detect small objects in real time. For depth estimation, we introduce binocular vision to the monocular-based disparity estimation network, and the epipolar constraint is used to improve prediction accuracy. Finally, we integrate the two-dimensional (2D) location of the detected object with the depth information to achieve real-time detection and depth estimation. The results demonstrate that the proposed approach achieves better results compared to conventional methods.

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Hasheminasab, M., H. Ebadi, and A. Sedaghat. "AN INTEGRATED RANSAC AND GRAPH BASED MISMATCH ELIMINATION APPROACH FOR WIDE-BASELINE IMAGE MATCHING." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-1-W5 (December 11, 2015): 297–300. http://dx.doi.org/10.5194/isprsarchives-xl-1-w5-297-2015.

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In this paper we propose an integrated approach in order to increase the precision of feature point matching. Many different algorithms have been developed as to optimizing the short-baseline image matching while because of illumination differences and viewpoints changes, wide-baseline image matching is so difficult to handle. Fortunately, the recent developments in the automatic extraction of local invariant features make wide-baseline image matching possible. The matching algorithms which are based on local feature similarity principle, using feature descriptor as to establish correspondence between feature point sets. To date, the most remarkable descriptor is the scale-invariant feature transform (SIFT) descriptor , which is invariant to image rotation and scale, and it remains robust across a substantial range of affine distortion, presence of noise, and changes in illumination. The epipolar constraint based on RANSAC (random sample consensus) method is a conventional model for mismatch elimination, particularly in computer vision. Because only the distance from the epipolar line is considered, there are a few false matches in the selected matching results based on epipolar geometry and RANSAC. Aguilariu et al. proposed Graph Transformation Matching (GTM) algorithm to remove outliers which has some difficulties when the mismatched points surrounded by the same local neighbor structure. In this study to overcome these limitations, which mentioned above, a new three step matching scheme is presented where the SIFT algorithm is used to obtain initial corresponding point sets. In the second step, in order to reduce the outliers, RANSAC algorithm is applied. Finally, to remove the remained mismatches, based on the adjacent K-NN graph, the GTM is implemented. Four different close range image datasets with changes in viewpoint are utilized to evaluate the performance of the proposed method and the experimental results indicate its robustness and capability.

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Cui, Zhaopeng, Guang Jiang, Shuai Yang, and Chengke Wu. "A new fast motion estimation algorithm based on the loop–epipolar constraint for multiview video coding." Signal Processing: Image Communication 27, no. 2 (February 2012): 172–79. http://dx.doi.org/10.1016/j.image.2011.11.001.

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Qayyum, Usman, and Jonghyuk Kim. "Depth-Camera-Aided Inertial Navigation Utilizing Directional Constraints." Sensors 21, no. 17 (September 2, 2021): 5913. http://dx.doi.org/10.3390/s21175913.

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This paper presents a practical yet effective solution for integrating an RGB-D camera and an inertial sensor to handle the depth dropouts that frequently happen in outdoor environments, due to the short detection range and sunlight interference. In depth drop conditions, only the partial 5-degrees-of-freedom pose information (attitude and position with an unknown scale) is available from the RGB-D sensor. To enable continuous fusion with the inertial solutions, the scale ambiguous position is cast into a directional constraint of the vehicle motion, which is, in essence, an epipolar constraint in multi-view geometry. Unlike other visual navigation approaches, this can effectively reduce the drift in the inertial solutions without delay or under small parallax motion. If a depth image is available, a window-based feature map is maintained to compute the RGB-D odometry, which is then fused with inertial outputs in an extended Kalman filter framework. Flight results from the indoor and outdoor environments, as well as public datasets, demonstrate the improved navigation performance of the proposed approach.

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Zhao, Ping, Yong Kui Li, and Shan Liang Xie. "Composite Measurement Method Based on Computer Vision Technology." Advanced Materials Research 418-420 (December 2011): 2118–21. http://dx.doi.org/10.4028/www.scientific.net/amr.418-420.2118.

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Based on analyzing current methods of acquiring point clouds data in reversing engineering, considering the features of structure light scanning and binocular stereovision, we proposed a composite measuring method based on vision technology, which combines the advantages of the two measurement methods in together, and established the measuring system. The greatest advantage of this method is that the edge data were obtained by binocular vision technology, and the internal data were obtained by Structure light method. In binocular vision, stereo matching was realized with the combination of epipolar constraint, corner feature matching and area matching, which could improve location precision and matching speed of feature point. An application example shows the composite measuring method is feasible.

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Hou, Ying, and Gui Cai Wang. "Research on Grain Storage Insect Image for Automatic Identification." Applied Mechanics and Materials 602-605 (August 2014): 1723–27. http://dx.doi.org/10.4028/www.scientific.net/amm.602-605.1723.

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According to prevention level of grain storage requirements and granary actual situation, a novel grain storage insect image for automatic identification algorithm was presented based on features point and stereo matching. Firstly, pyramid delaminating was used to preprocess target image. Then, image normalized could be obtained according to formula. Secondly, the SIFT features points could be extracted from reference image and target image. Finally, according to epipolar constraint and the straight line slope of pass through features matching points, The paper could be successful to automatic identify grain storage insect. The results of experiment with the really grain storage insect images shown the proposed algorithm was effective and could obtain high recognition rate.

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Xiong, J., S. Zhong, and L. Zheng. "AN AUTOMATIC 3D RECONSTRUCTION METHOD BASED ON MULTI-VIEW STEREO VISION FOR THE MOGAO GROTTOES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-4/W5 (May 11, 2015): 171–76. http://dx.doi.org/10.5194/isprsarchives-xl-4-w5-171-2015.

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This paper presents an automatic three-dimensional reconstruction method based on multi-view stereo vision for the Mogao Grottoes. 3D digitization technique has been used in cultural heritage conservation and replication over the past decade, especially the methods based on binocular stereo vision. However, mismatched points are inevitable in traditional binocular stereo matching due to repeatable or similar features of binocular images. In order to reduce the probability of mismatching greatly and improve the measure precision, a portable four-camera photographic measurement system is used for 3D modelling of a scene. Four cameras of the measurement system form six binocular systems with baselines of different lengths to add extra matching constraints and offer multiple measurements. Matching error based on epipolar constraint is introduced to remove the mismatched points. Finally, an accurate point cloud can be generated by multi-images matching and sub-pixel interpolation. Delaunay triangulation and texture mapping are performed to obtain the 3D model of a scene. The method has been tested on 3D reconstruction several scenes of the Mogao Grottoes and good results verify the effectiveness of the method.

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Feng, Guanyuan, Lin Ma, Xuezhi Tan, Hao Xue, and Kai Guan. "Visual Location Recognition Based on Coarse-to-Fine Image Retrieval and Epipolar Geometry Constraint for Urban Environment." International Journal of Signal Processing, Image Processing and Pattern Recognition 9, no. 11 (November 30, 2016): 25–36. http://dx.doi.org/10.14257/ijsip.2016.9.11.03.

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He, Pan Li, and Wen Lin Liu. "Research on River Channel Terrain Measurement Method Based on Binocular Vision." Applied Mechanics and Materials 239-240 (December 2012): 717–20. http://dx.doi.org/10.4028/www.scientific.net/amm.239-240.717.

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For the existed river channel terrain measurement method defects such as complex measurement process and high performance equipments requirement, in the paper a terrain measurement method based on binocular vision is proposed. Firstly, in proposed system binocular vision measurement parameters are calculated on the basis of monocular calibration; secondly, artificial signs are located in river channel and detected based on improved Harris corners detection algorithm; thirdly, the feature corners in binocular images are matched based on epipolar constraint and SIFT algorithm; finally, for corrected images feature corners location method is proposed, and the river channel terrain is measured. Experiments show that in the proposed method the river channel terrain can be measured accurately, and the method has good reference value to measure other irregular scenes.

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Li, Da Cheng, Jin Liang, Hao Hu, Zheng Zong Tang, Xiang Guo, and Lei Gang Li. "Strain Measurement for Sheet Metal Forming Based on Close Range Photogrammetry." Applied Mechanics and Materials 475-476 (December 2013): 148–55. http://dx.doi.org/10.4028/www.scientific.net/amm.475-476.148.

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To improve efficiency and automation of the 3D full-field surface strain measurement for sheet metal forming, a new grid strain measuring scheme was developed based on the close-range photogrammetry technology. A Local Canny Detector algorithm was proposed for grid nodes and coded targets detection. A 10-parameters nonlinear camera model and the bundle adjustment algorithm were used to optimize the calibration parameters. A multi-epipolar constraint method was employed for grid node matching. Finally, the surface strains were calculated according to the changes of the grid sizes. To evaluate the performance of the proposed scheme, a stamping forming experiment was conducted. Experimental results show that the scheme can provide a non-contact, intuitive and effective solution for strain measurement in sheet metal forming process.

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