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Journal articles on the topic 'Correspondence estimation'

Author: Grafiati

Published: 25 May 2024

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1

Liu, Yizhang, Shengjie Zhao, Hao Deng, and Fuqiang Ding. "Correspondence Learning via Correspondence Embedded and Channel Recalibration Network." ITM Web of Conferences 60 (2024): 00008. http://dx.doi.org/10.1051/itmconf/20246000008.

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Correspondence learning is pivotal to many computer vision-based tasks. Existing methods regard each correspondence equally along the channel dimension, which weakens the feature representation capability of the network. To alleviate this problem, we propose a Correspondence Embedded and Channel Recalibration Network, named CECR-Net, to predict the inlier probability of each correspondence and recover camera poses. The proposed CECR-Net is designed to explore the potential impact of correspondences on the channel dimension, and recalibrate the weight of each channel, so that our CECRNet can ca

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Huang, Zhaoyang, Xiaokun Pan, Weihong Pan, et al. "NeuralMarker." ACM Transactions on Graphics 41, no. 6 (2022): 1–10. http://dx.doi.org/10.1145/3550454.3555468.

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We tackle the problem of estimating correspondences from a general marker, such as a movie poster, to an image that captures such a marker. Conventionally, this problem is addressed by fitting a homography model based on sparse feature matching. However, they are only able to handle plane-like markers and the sparse features do not sufficiently utilize appearance information. In this paper, we propose a novel framework NeuralMarker, training a neural network estimating dense marker correspondences under various challenging conditions, such as marker deformation, harsh lighting, etc. Deep learn

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Zhang, Shihua, and Jiayi Ma. "ConvMatch: Rethinking Network Design for Two-View Correspondence Learning." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 3 (2023): 3472–79. http://dx.doi.org/10.1609/aaai.v37i3.25456.

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Multilayer perceptron (MLP) has been widely used in two-view correspondence learning for only unordered correspondences provided, and it extracts deep features from individual correspondence effectively. However, the problem of lacking context information limits its performance and hence, many extra complex blocks are designed to capture such information in the follow-up studies. In this paper, from a novel perspective, we design a correspondence learning network called ConvMatch that for the first time can leverage convolutional neural network (CNN) as the backbone to capture better context,

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Fu, Mingliang, and Weijia Zhou. "DeepHMap++: Combined Projection Grouping and Correspondence Learning for Full DoF Pose Estimation." Sensors 19, no. 5 (2019): 1032. http://dx.doi.org/10.3390/s19051032.

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In recent years, estimating the 6D pose of object instances with convolutional neural network (CNN) has received considerable attention. Depending on whether intermediate cues are used, the relevant literature can be roughly divided into two broad categories: direct methods and two-stage pipelines. For the latter, intermediate cues, such as 3D object coordinates, semantic keypoints, or virtual control points instead of pose parameters are regressed by CNN in the first stage. Object pose can then be solved by correspondence constraints constructed with these intermediate cues. In this paper, we

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Dai, Luanyuan, Xin Liu, Jingtao Wang, Changcai Yang, and Riqing Chen. "Learning Two-View Correspondences and Geometry via Local Neighborhood Correlation." Entropy 23, no. 8 (2021): 1024. http://dx.doi.org/10.3390/e23081024.

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Seeking quality feature correspondences (also known as matches) is a foundational step in computer vision. In our work, a novel and effective network with a stable local constraint, named the Local Neighborhood Correlation Network (LNCNet), is proposed to capture abundant contextual information of each correspondence in the local region, followed by calculating the essential matrix and camera pose estimation. Firstly, the k-Nearest Neighbor (KNN) algorithm is used to divide the local neighborhood roughly. Then, we calculate the local neighborhood correlation matrix (LNC) between the selected c

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Redert, A., E. Hendriks, and J. Biemond. "Correspondence estimation in image pairs." IEEE Signal Processing Magazine 16, no. 3 (1999): 29–46. http://dx.doi.org/10.1109/79.768571.

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YAMASHINA, Hideki, Akihiro ICHIHASHI, Atushi KURODA, and Koichi IKEDA. "ESTIMATION OF COLOR RENDERING INDICES WITH CORRESPONDENCE TO PERCEIVED COLOR SHIFTS." JOURNAL OF THE ILLUMINATING ENGINEERING INSTITUTE OF JAPAN 78, Appendix (1994): 377–78. http://dx.doi.org/10.2150/jieij1980.78.appendix_377.

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Pons-Moll, Gerard, Jonathan Taylor, Jamie Shotton, Aaron Hertzmann, and Andrew Fitzgibbon. "Metric Regression Forests for Correspondence Estimation." International Journal of Computer Vision 113, no. 3 (2015): 163–75. http://dx.doi.org/10.1007/s11263-015-0818-9.

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Yi, Yunai, Diya Sun, Peixin Li, Tae-Kyun Kim, Tianmin Xu, and Yuru Pei. "Unsupervised random forest for affinity estimation." Computational Visual Media 8, no. 2 (2021): 257–72. http://dx.doi.org/10.1007/s41095-021-0241-9.

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AbstractThis paper presents an unsupervised clustering random-forest-based metric for affinity estimation in large and high-dimensional data. The criterion used for node splitting during forest construction can handle rank-deficiency when measuring cluster compactness. The binary forest-based metric is extended to continuous metrics by exploiting both the common traversal path and the smallest shared parent node.The proposed forest-based metric efficiently estimates affinity by passing down data pairs in the forest using a limited number of decision trees. A pseudo-leaf-splitting (PLS) algorit

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Tang, Jiexiong, John Folkesson, and Patric Jensfelt. "Geometric Correspondence Network for Camera Motion Estimation." IEEE Robotics and Automation Letters 3, no. 2 (2018): 1010–17. http://dx.doi.org/10.1109/lra.2018.2794624.

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11

Han, Li, Dan Li, Shu Ning Liu, Yu Nan Liu, and Di Tang. "Similarity estimation based on sparse spectral correspondence." Multimedia Tools and Applications 78, no. 11 (2018): 14443–63. http://dx.doi.org/10.1007/s11042-018-6623-z.

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12

Hödel, M., T. Koch, L. Hoegner, and U. Stilla. "MONOCULAR-DEPTH ASSISTED SEMI-GLOBAL MATCHING." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences IV-2/W7 (September 16, 2019): 55–62. http://dx.doi.org/10.5194/isprs-annals-iv-2-w7-55-2019.

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<p><strong>Abstract.</strong> Reconstruction of dense photogrammetric point clouds is often based on depth estimation of rectified image pairs by means of pixel-wise matching. The main drawback lies in the high computational complexity compared to that of the relatively straightforward task of laser triangulation. Dense image matching needs oriented and rectified images and looks for point correspondences between them. The search for these correspondences is based on two assumptions: pixels and their local neighborhood show a similar radiometry and image scenes are mostly hom

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Fan, Yingruo, Jacqueline Lam, and Victor Li. "Facial Action Unit Intensity Estimation via Semantic Correspondence Learning with Dynamic Graph Convolution." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 07 (2020): 12701–8. http://dx.doi.org/10.1609/aaai.v34i07.6963.

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The intensity estimation of facial action units (AUs) is challenging due to subtle changes in the person's facial appearance. Previous approaches mainly rely on probabilistic models or predefined rules for modeling co-occurrence relationships among AUs, leading to limited generalization. In contrast, we present a new learning framework that automatically learns the latent relationships of AUs via establishing semantic correspondences between feature maps. In the heatmap regression-based network, feature maps preserve rich semantic information associated with AU intensities and locations. Moreo

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Valeriy, Khabarov, Tesselkin Alexandr, and Kosolapov Kirill. "Design of experiments for transport correspondence matrix estimation." Proceedings of the Russian higher school Academy of sciences, no. 3 (September 21, 2015): 109–16. http://dx.doi.org/10.17212/1727-2769-2015-3-109-116.

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Besse, Frederic, Carsten Rother, Andrew Fitzgibbon, and Jan Kautz. "PMBP: PatchMatch Belief Propagation for Correspondence Field Estimation." International Journal of Computer Vision 110, no. 1 (2013): 2–13. http://dx.doi.org/10.1007/s11263-013-0653-9.

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Castillo, Louise IR, M. Erin Browne, Thomas Hadjistavropoulos, Kenneth M. Prkachin, and Rafik Goubran. "Automated vs. manual pain coding and heart rate estimations based on videos of older adults with and without dementia." Journal of Rehabilitation and Assistive Technologies Engineering 7 (January 2020): 205566832095019. http://dx.doi.org/10.1177/2055668320950196.

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Introduction Technological advances have allowed for the estimation of physiological indicators from video data. FaceReader™ is an automated facial analysis software that has been used widely in studies of facial expressions of emotion and was recently updated to allow for the estimation of heart rate (HR) using remote photoplethysmography (rPPG). We investigated FaceReader™-based heart rate and pain expression estimations in older adults in relation to manual coding by experts. Methods Using a video dataset of older adult patients with and without dementia, we assessed the relationship betwee

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Krak, Yu V., O. V. Barmak, and O. V. Mazurets. "The practice investigation of the information technology efficiency for automated definition of terms in the semantic content of educational materials." PROBLEMS IN PROGRAMMING, no. 2-3 (June 2016): 237–45. http://dx.doi.org/10.15407/pp2016.02-03.237.

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The information technology on base of the disperse evaluation, which with enough high efficiency allows automated define the semantic terms in content of educational materials article is given. The factors that hinder effective analysis of educational materials have been considered. High efficiency offered technologies gives possible of its using in row of the problems, such as estimation of the correspondence of educational materials to requirements, estimation of the correspondence of set test tasks to educational materials, semantic help of making tests, automated keyword list and abstract

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18

LIU, Y., and M. A. RODRIGUES. "INVARIANT GEOMETRIC PROPERTIES OF IMAGE CORRESPONDENCE VECTORS AS RIGID CONSTRAINTS TO MOTION ESTIMATION." International Journal of Pattern Recognition and Artificial Intelligence 13, no. 08 (1999): 1165–79. http://dx.doi.org/10.1142/s0218001499000665.

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Accurate motion estimation algorithms are based on a number of invariant properties that can be inferred from the motion. A large number of calibration algorithms have been proposed over the last two decades mainly based on analytic, perspective, or epipolar geometries. Extending Chasles' screw motion concept to the estimation of motion parameters in computer vision, we have presented an analysis of geometric properties of image correspondence vectors synthesized into a single coordinate frame and developed calibration algorithms using both simulated and real range image data.15,16 In this pap

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Shao, Huixiang, Zhijiang Zhang, Xiaoyu Feng, and Dan Zeng. "SCRnet: A Spatial Consistency Guided Network Using Contrastive Learning for Point Cloud Registration." Symmetry 14, no. 1 (2022): 140. http://dx.doi.org/10.3390/sym14010140.

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Point cloud registration is used to find a rigid transformation from the source point cloud to the target point cloud. The main challenge in the point cloud registration is in finding correct correspondences in complex scenes that may contain many noise and repetitive structures. At present, many existing methods use outlier rejections to help the network obtain more accurate correspondences, but they often ignore the spatial consistency between keypoints. Therefore, to address this issue, we propose a spatial consistency guided network using contrastive learning for point cloud registration (

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20

Martynenko, A. V., and A. A. Shevtsov. "Estimation of the passenger correspondence matrix using the least squares method to calibrate the gravity model." Herald of the Ural State University of Railway Transport, no. 4 (2021): 4–13. http://dx.doi.org/10.20291/2079-0392-2021-4-4-13.

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The matrix of passenger correspondence plays a key role in many issues of planning and forecasting the development of the transport system. Usually, a gravitational model is used to evaluate the correspondence matrix. The specification and calibration method of the gravity model depends on what data is known from observations. In particular, if the volumes of departures and arrivals for each point and the average cost (duration) of the trip are known, then a gravitational model with an exponential gravity function is used, and the Hyman method is used to calibrate it. If the correspondence mat

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21

Fokov, O. A/. "Analysis of the state of the art in the problem of determining the pose of on-orbit service objects." Technical mechanics 2023, no. 1 (2023): 54–67. http://dx.doi.org/10.15407/itm2023.01.054.

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Recently considerable attention has been paid to the problem of estimating the pose of an on-orbit service object. Determining the pose at a close distance still remains an open line of research, especially for non-cooperative objects (targets) of on-orbit service. The goal of this work is to overview the state of the art in the problem of determining the relative motion parameters of on-orbit service objects with emphasis on close proximity operations with non-cooperative and unknown targets. The method employed is the analysis of publications devoted to this problem over the last decade. The

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Schweizer, Karl, Stefan Troche, and Siegbert Reiß. "Can Variances of Latent Variables be Scaled in Such a Way That They Correspond to Eigenvalues?" International Journal of Statistics and Probability 6, no. 6 (2017): 35. http://dx.doi.org/10.5539/ijsp.v6n6p35.

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The paper reports an investigation of whether sums of squared factor loadings obtained in confirmatory factor analysis correspond to eigenvalues of exploratory factor analysis. The sum of squared factor loadings reflects the variance of the corresponding latent variable if the variance parameter of the confirmatory factor model is set equal to one. Hence, the computation of the sum implies a specific type of scaling of the variance. While the investigation of the theoretical foundations suggested the expected correspondence between sums of squared factor loadings and eigenvalues, the necessity

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23

Bian, Jia-Wang, Wen-Yan Lin, Yun Liu, et al. "GMS: Grid-Based Motion Statistics for Fast, Ultra-robust Feature Correspondence." International Journal of Computer Vision 128, no. 6 (2019): 1580–93. http://dx.doi.org/10.1007/s11263-019-01280-3.

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AbstractFeature matching aims at generating correspondences across images, which is widely used in many computer vision tasks. Although considerable progress has been made on feature descriptors and fast matching for initial correspondence hypotheses, selecting good ones from them is still challenging and critical to the overall performance. More importantly, existing methods often take a long computational time, limiting their use in real-time applications. This paper attempts to separate true correspondences from false ones at high speed. We term the proposed method (GMS) grid-based motion S

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Tsai, Chi-Yi, Kuang-Jui Hsu, and Humaira Nisar. "Efficient Model-Based Object Pose Estimation Based on Multi-Template Tracking and PnP Algorithms." Algorithms 11, no. 8 (2018): 122. http://dx.doi.org/10.3390/a11080122.

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Three-Dimensional (3D) object pose estimation plays a crucial role in computer vision because it is an essential function in many practical applications. In this paper, we propose a real-time model-based object pose estimation algorithm, which integrates template matching and Perspective-n-Point (PnP) pose estimation methods to deal with this issue efficiently. The proposed method firstly extracts and matches keypoints of the scene image and the object reference image. Based on the matched keypoints, a two-dimensional (2D) planar transformation between the reference image and the detected obje

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Hama, Katsumi, and Yukinori Kakazu. "Motion Estimation of Object based on Three-Dimensional Correspondence." Journal of the Japan Society for Precision Engineering 59, no. 2 (1993): 222–26. http://dx.doi.org/10.2493/jjspe.59.222.

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26

Laskov, P., and C. Kambhamettu. "Curvature-based algorithms for nonrigid motion and correspondence estimation." IEEE Transactions on Pattern Analysis and Machine Intelligence 25, no. 10 (2003): 1349–54. http://dx.doi.org/10.1109/tpami.2003.1233911.

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27

Li, Shaoxin, Xin Liu, Xiujuan Chai, Haihong Zhang, Shihong Lao, and Shiguang Shan. "Maximal Likelihood Correspondence Estimation for Face Recognition Across Pose." IEEE Transactions on Image Processing 23, no. 10 (2014): 4587–600. http://dx.doi.org/10.1109/tip.2014.2351265.

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28

Chen, Pengwen. "A Novel Kernel Correlation Model with the Correspondence Estimation." Journal of Mathematical Imaging and Vision 39, no. 2 (2010): 100–120. http://dx.doi.org/10.1007/s10851-010-0230-6.

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29

Lin, Wen-Yan, Loong-Fah Cheong, Ping Tan, Guo Dong, and Siying Liu. "Simultaneous Camera Pose and Correspondence Estimation with Motion Coherence." International Journal of Computer Vision 96, no. 2 (2011): 145–61. http://dx.doi.org/10.1007/s11263-011-0456-9.

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Yang, Haiwei, Fei Wang, Zhe Li, and Hang Dong. "Simultaneous Pose and Correspondence Estimation Based on Genetic Algorithm." International Journal of Distributed Sensor Networks 11, no. 11 (2015): 828241. http://dx.doi.org/10.1155/2015/828241.

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Gajewski, Byron J., and Clifford H. Spiegelman. "Correspondence estimation of the source profiles in receptor modeling." Environmetrics 15, no. 6 (2004): 613–34. http://dx.doi.org/10.1002/env.654.

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Hosseini, Morteza Darvish Morshedi, Miroslav Goljan, and Hui Zeng. "Semi-Blind Image Resampling Factor Estimation for PRNU Computation." Electronic Imaging 2020, no. 4 (2020): 77–1. http://dx.doi.org/10.2352/issn.2470-1173.2020.4.mwsf-077.

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Camera sensor fingerprints for digital camera forensics are formed by Photo-Response Non-Uniformity (PRNU), or more precisely, by estimating PRNU from a set of images taken with a camera. These images must be aligned with each other to establish sensor location pixel-to-pixel correspondence. If some of these images have been resized and cropped, the transformations need to be reversed. In this work we deal with estimation of resizing factor in the presence of one reference image from the same camera. For this problem we coin the term semi-blind estimation of resizing factor. We post two requir

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33

Katsulai, Hiroshi. "Extraction and Motion Estimation of 3D Objects from Stereo Image Sequence." Journal of Robotics and Mechatronics 8, no. 6 (1996): 561–70. http://dx.doi.org/10.20965/jrm.1996.p0561.

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It is important to estimate motion parameters and structures of 3D objects from the image sequence, and a variety of methods to do so have been proposed so far. In this paper, a method is described of estimating the motion and structure of a 3D object from the stereo image sequence. In this method, based on the correspondence of 2D segments in each stereo pair, using a newly devised similarity measure, 3D segments are reconstructed, then grouped into rigid objects, making use of the correspondence of 3D segments in successive images, and parameters of rigid motions are computed for each group.

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Batra, Deepak, Sanjay Sharma, and Amit Kumar Kohli. "Improved Parameter Estimation for First-Order Markov Process." Research Letters in Signal Processing 2009 (2009): 1–2. http://dx.doi.org/10.1155/2009/186250.

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This correspondence presents a linear transformation, which is used to estimate correlation coefficient of first-order Markov process. It outperforms zero-forcing (ZF), minimum mean-squared error (MMSE), and whitened least-squares (WTLSs) estimators by controlling output noise variance at the cost of increased computational complexity.

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ELHADY, GAMAL F. "3D STRUCTURE FROM MOTION WITH FOURIER DESCRIPTOR TRANSFORMATION." International Journal of Pattern Recognition and Artificial Intelligence 27, no. 05 (2013): 1355006. http://dx.doi.org/10.1142/s0218001413550069.

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The simultaneous recovery of three-dimensional (3D) structure from motion (SfM) for the sequences of images, is one of the more difficult problems in computer vision. Classical approaches to the problem rely on using algebraic techniques to solve for these unknowns given two or more image. Motion analysis and 3D shape estimation based on the estimated motion is an important problem in computer vision. The correspondence problem is an important tool in SfM where in this paper a general 3D motion based on a simple rotation, tilt, roll and translation is proposed, and then is used for 3D shape es

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Du, Shitong, Helge A. Lauterbach, Xuyou Li, Girum G. Demisse, Dorit Borrmann, and Andreas Nüchter. "Curvefusion—A Method for Combining Estimated Trajectories with Applications to SLAM and Time-Calibration." Sensors 20, no. 23 (2020): 6918. http://dx.doi.org/10.3390/s20236918.

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Mapping and localization of mobile robots in an unknown environment are essential for most high-level operations like autonomous navigation or exploration. This paper presents a novel approach for combining estimated trajectories, namely curvefusion. The robot used in the experiments is equipped with a horizontally mounted 2D profiler, a constantly spinning 3D laser scanner and a GPS module. The proposed algorithm first combines trajectories from different sensors to optimize poses of the planar three degrees of freedom (DoF) trajectory, which is then fed into continuous-time simultaneous loca

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García, Bryan, Carlos Diego Ferrin B., and Jorge Humberto Erazo. "3D reconstruction system for semi-automatic estimation of objects length and area by means of stereo vision." Sistemas y Telemática 15, no. 40 (2017): 27–39. http://dx.doi.org/10.18046/syt.v15i40.2372.

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It is mandatory to characterize dimensionally the manufactured industrial pieces for quality control purposes. As it is not possible to touch some pieces when trying to retrieve dimensional information, then non-invasive techniques are required to do so. Stereo vision is a passive technology which is both robust and accurate for non-invasive applications. For this reason, in this work we describe the design and implementation of a 3D reconstruction system for the estimation of the length and area of certain objects. This tool allows to easily incorporate new image correspondence techniques to

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A., Deepambika V., and M. Abdul Rahiman. "Radiometric Invariant Dense Disparity Estimation for Real Time Stereo Correspondence." Journal of Computer Science 15, no. 4 (2019): 450–62. http://dx.doi.org/10.3844/jcssp.2019.450.462.

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Chi-Ying Tsui, J. Monteiro, M. Pedram, S. Devadas, A. M. Despain, and B. Lin. "Correction to "Power Estimation Methods for Sequential Logic Circuits" [Correspondence]." IEEE Transactions on Very Large Scale Integration (VLSI) Systems 4, no. 4 (1996): 495. http://dx.doi.org/10.1109/tvlsi.1996.544414.

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Sunghwan Choi, Dongbo Min, Bumsub Ham, and Kwanghoon Sohn. "Unsupervised Texture Flow Estimation Using Appearance-Space Clustering and Correspondence." IEEE Transactions on Image Processing 24, no. 11 (2015): 3652–65. http://dx.doi.org/10.1109/tip.2015.2449078.

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Jeong, Hyundoo, and Byung-Jun Yoon. "Effective Estimation of Node-to-Node Correspondence Between Different Graphs." IEEE Signal Processing Letters 22, no. 6 (2015): 661–65. http://dx.doi.org/10.1109/lsp.2014.2366051.

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Zhang, Feihu, Shibiao Xu, and Xiaopeng Zhang. "High accuracy correspondence field estimation via MST based patch matching." Multimedia Tools and Applications 79, no. 19-20 (2020): 13291–309. http://dx.doi.org/10.1007/s11042-020-08633-y.

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Liu, JinBo, XiaoHu Zhang, HaiBo Liu, Yun Yuan, ZhaoKun Zhu, and QiFeng Yu. "New method for camera pose estimation based on line correspondence." Science China Technological Sciences 56, no. 11 (2013): 2787–97. http://dx.doi.org/10.1007/s11431-013-5361-8.

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Liu, Yuncai, and Thomas S. Huang. "A linear algorithm for motion estimation using straight line correspondence." Computer Vision, Graphics, and Image Processing 43, no. 3 (1988): 432. http://dx.doi.org/10.1016/0734-189x(88)90093-x.

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Leng, D. W., and W. D. Sun. "Iterative three-dimensional rigid object pose estimation with contour correspondence." IET Image Processing 6, no. 5 (2012): 569. http://dx.doi.org/10.1049/iet-ipr.2010.0435.

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Li, Shenghao, Qunfei Zhao, and Zeyang Xia. "Sparse-to-Local-Dense Matching for Geometry-Guided Correspondence Estimation." IEEE Transactions on Image Processing 32 (2023): 3536–51. http://dx.doi.org/10.1109/tip.2023.3287500.

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Tomaževič, Dejan, Boštjan Likar, and Franjo Pernuš. "MULTI-FEATURE MUTUAL INFORMATION IMAGE REGISTRATION." Image Analysis & Stereology 31, no. 1 (2012): 43. http://dx.doi.org/10.5566/ias.v31.p43-53.

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Nowadays, information-theoretic similarity measures, especially the mutual information and its derivatives, are one of the most frequently used measures of global intensity feature correspondence in image registration. Because the traditional mutual information similarity measure ignores the dependency of intensity values of neighboring image elements, registration based on mutual information is not robust in cases of low global intensity correspondence. Robustness can be improved by adding spatial information in the form of local intensity changes to the global intensity correspondence. This

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48

Lebedeva, Ol'ga. "COMPARATIVE ANALYSIS OF EXISTING METHODS FOR DEVELOPING CORRESPONDENCE MATRICES." Modern Technologies and Scientific and Technological Progress 1, no. 1 (2021): 181–82. http://dx.doi.org/10.36629/2686-9896-2021-1-1-181-182.

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The study is aimed at comparing the methods of restoring correspondence matri ces, the traditional transport school and modern mobile technologies. Traditionally, correspondence  matrices are restored by interviewing vehicle drivers and applying gravity models (to extrapolate and  fill in unobserved movements), then matrix estimation methods are used to calculate traffic flows.  Each of these approaches has a number of advantages and disadvantages, but there is no evidence  to assess the quality of the data obtained.

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LEI, B. J., LI-QUN XU, E. A. HENDRIKS, and J. BIEMOND. "ROBUSTLY ESTIMATING DISPARITY FROM ADAPTIVE DENSE CURVES." International Journal of Pattern Recognition and Artificial Intelligence 17, no. 07 (2003): 1081–109. http://dx.doi.org/10.1142/s0218001403002836.

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In this paper, we propose a novel area-based algorithm for stereo correspondence estimation. The new dense correspondence estimation algorithm, which we call HACM (Hierarchical Adaptive Curve Matching), is suitable for stereo analysis of both static and dynamic scenes. The core of this method is the derivation of a pixel-based dense adaptive curve representation. For each pixel in the concerned 2-D images, the changes are characterized roughly in the local surface shape, the texture direction, and the luminance properties, all at a slight overhead cost. The matching is carried out in a hierarc

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Ondrašovič, Milan, and Peter Tarábek. "Homography Ranking Based on Multiple Groups of Point Correspondences." Sensors 21, no. 17 (2021): 5752. http://dx.doi.org/10.3390/s21175752.

Full text

Abstract:

Homography mapping is often exploited to remove perspective distortion in images and can be estimated using point correspondences of a known object (marker). We focus on scenarios with multiple markers placed on the same plane if their relative positions in the world are unknown, causing an indeterminate point correspondence. Existing approaches may only estimate an isolated homography for each marker and cannot determine which homography achieves the best reprojection over the entire image. We thus propose a method to rank isolated homographies obtained from multiple distinct markers to selec

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