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Journal articles on the topic '3D Shape Matching'

Author: Grafiati
Published: 4 June 2025
Last updated: 15 July 2025

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1

Avagyan, Vahram, Armen Zakarian, and Pravansu Mohanty. "Scanned Three-Dimensional Model Matching and Comparison Algorithms for Manufacturing Applications." Journal of Manufacturing Science and Engineering 129, no. 1 (2006): 190–201. http://dx.doi.org/10.1115/1.2375139.

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In recent years the increased use of 3D scanning hardware has introduced a new type of data to the design and manufacturing field. In many design and manufacturing applications (e.g., part refurbishing or remanufacturing) a scanned 3D model may be provided as an input to a shape matching system to search the database for related or identical models with the purpose of extracting useful information. The introduction of scanned 3D models restricts the use of the CAD-based 3D model search and comparison methods due to significant differences in model representations. The CAD models provide structured and high-level representation of the part features, whereas the scanned 3D models usually come in a polygonal mesh representation, which does not directly reveal engineering features of the part. These differences require new algorithms for comparing the shapes of scanned 3D models, ones that are robust against different scanning technologies and can be adjusted to work with different representations of the models. In this paper, a new approach and algorithms for scanned 3D shape matching and comparison are presented. Given the scanned 3D model as an input the approach first uses general-purpose shape matching methods to identify a small list of likely matches (i.e., candidate models) for more detailed shape comparison. To perform detailed comparison of the shapes each candidate model is geometrically adjusted (i.e., rotated and translated) with the input using one of two new viewpoint algorithms developed in this paper. Once the candidate models are adjusted they are compared to the input to identify the similarities and differences between their shapes. To accomplish this task a new 3D shape matching algorithm is developed. The relevance of the methodology developed in this paper is illustrated with the application of scanned 3D shape matching and comparison algorithms in rapid manufacturing of broken parts.
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Bai, Xiang, Song Bai, Zhuotun Zhu, and Longin Jan Latecki. "3D Shape Matching via Two Layer Coding." IEEE Transactions on Pattern Analysis and Machine Intelligence 37, no. 12 (2015): 2361–73. http://dx.doi.org/10.1109/tpami.2015.2424863.

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3

Arhid, K., F. R. Zakani, M. Bouksim, B. Sirbal, M. Aboulfatah, and T. Gad. "A novel approach for partial shape matching and similarity based on data envelopment analysis." Computer Optics 43, no. 2 (2019): 316–23. http://dx.doi.org/10.18287/2412-6179-2019-43-2-316-323.

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Due to the growing number of 3D objects in digital libraries, the task of searching and browsing models in an extensive 3D database has been the focus of considerable research in the area. In the last decade, several approaches to retrieve 3D models based on shape similarity have been proposed. The majority of the existing methods addresses the problem of similarity between objects as a global matching problem. Consequently, most of these techniques do not support a part of the object as a query, in addition to their poor performance for classes with globally non-similar shape models and also for articulated objects. The partial matching technique seems to be a suitable solution to these problems. In this paper, we address the problem of shape matching and retrieval. We propose a new approach based on partial matching in which each 3D object is segmented into its constituent parts, and shape descriptors are computed from these elements to compare similarities. Several experiments investigated that our technique enables fast computing for content-based 3D shape retrieval and significantly improves the results of our method based on Data Envelopment Analysis descriptor for global matching.
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Langenfeld, Peng, Lai, et al. "SHREC 2020: Multi-domain protein shape retrieval challenge." Computer & Graphics 91 (July 15, 2020): 189–98. https://doi.org/10.1016/j.cag.2020.07.013.

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Proteins are natural modular objects usually composed of several domains, each domain bearing a spe- cific function that is mediated through its surface, which is accessible to vicinal molecules. This draws attention to an understudied characteristic of protein structures: surface, that is mostly unexploited by protein structure comparison methods. In the present work, we evaluated the performance of six shape comparison methods, among which three are based on machine learning, to distinguish between 588 multi-domain proteins and to recreate the evolutionary relationships at the protein and species levels of the SCOPe database. The six groups that participated in the challenge submitted a total of 15 sets of results. We observed that the performance of all the methods significantly decreases at the species level, suggesting that shape-only protein comparison is challenging for closely related proteins. Even if the dataset is limited in size (only 588 proteins are considered whereas more than 160,0 0 0 protein structures are experimentally solved), we think that this work provides useful insights into the current shape comparison methods performance, and highlights possible limitations to large-scale applications due to the computational cost.
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Zhu, Geng Ming, and Xiao Fei Zhou. "3D Reconstruction and Analysis Base on Shape Matching." Applied Mechanics and Materials 380-384 (August 2013): 1868–72. http://dx.doi.org/10.4028/www.scientific.net/amm.380-384.1868.

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The article presents an approach to the three-dimensional reconstruction of vertebral column based on shape matching. Technique is established on the basis of marching cubes algorithm, through the rotated transformation and perspective projection toward every 3D model of vertebration, the projection drawing which is similar to the corresponding vertebration in the computed tomography is formed. Then, through the matching of the projection drawing and the corresponding vertebration in the CT, we can obtain the experimental result by adjust rotation parameters according to the matching outcome. The last step is to record the rotation parameters α, β and the translation parameters h, v, and by justifying the according parameter of the vertebration model in the standard vertebral column model based upon the circumgyrate of every vertebra and the translation parameters, the post-model of vertebration is reconstructed by means of visualization technology. The experimental result turned out that the reconstructed 3D model has a commendable matching attribute and meticulous accuracy compared with the real spinal column. Even the quality of the experimental CT is not so satisfied, the technique can still process match and reestablish the exact model column.
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Vergeest, Joris S. M., Sander Spanjaard, Imre Horva´th, and Jos J. O. Jelier. "Fitting Freeform Shape Patterns to Scanned 3D Objects." Journal of Computing and Information Science in Engineering 1, no. 3 (2001): 218–24. http://dx.doi.org/10.1115/1.1419197.

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This paper describes a new approach to locate freeform shape patterns in measured point data and to fit their parameter values. The method is based on the direct matching of parameterized shape templates to digitized points. For a given class of feature, the optimal pose and the optimal intrinsic shape parameters are determined. Although this principle was previously used in digital image processing and also for fitting of regular shaped features, it has rarely been applied in 3D to freeform features. Yet, several engineering applications may profit from improved feature fitting. The motivation of our investigation is to enable the reuse of precedent shapes, available in the form of physical parts. We aim at an extension to what is generally known as reverse engineering of shape. However, the proposed technique can also be used to extract feature parameters from imported CAD models. This paper addresses computational aspects of the method and presents the algorithms, implementation tests and numerical results.
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7

Attene, M., S. Marini, M. Spagnuolo, and B. Falcidieno. "Part-in-whole 3D shape matching and docking." Visual Computer 27, no. 11 (2011): 991–1004. http://dx.doi.org/10.1007/s00371-011-0622-7.

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Koutsoudis, Anestis, and Christodoulos Chamzas. "3D pottery shape matching using depth map images." Journal of Cultural Heritage 12, no. 2 (2011): 128–33. http://dx.doi.org/10.1016/j.culher.2010.12.003.

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9

Sun, Xiao-Peng, Si-Hui Li, Feng Han та Xiao-Peng Wei. "3D Ear Shape Matching Using Joint α-Entropy". Journal of Computer Science and Technology 30, № 3 (2015): 565–77. http://dx.doi.org/10.1007/s11390-015-1546-x.

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10

Du, Guo-Guang, Cong-Li Yin, Ming-Quan Zhou, et al. "Isometric 3D Shape Partial Matching Using GD-DNA." Journal of Computer Science and Technology 33, no. 6 (2018): 1178–91. http://dx.doi.org/10.1007/s11390-018-1880-x.

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Guan, Zhihao, Ruixin Liu, Zejian Yuan, et al. "Flexible 3D Lane Detection by Hierarchical Shape Matching." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 1 (2023): 694–701. http://dx.doi.org/10.1609/aaai.v37i1.25146.

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As one of the basic while vital technologies for HD map construction, 3D lane detection is still an open problem due to varying visual conditions, complex typologies, and strict demands for precision. In this paper, an end-to-end flexible and hierarchical lane detector is proposed to precisely predict 3D lane lines from point clouds. Specifically, we design a hierarchical network predicting flexible representations of lane shapes at different levels, simultaneously collecting global instance semantics and avoiding local errors. In the global scope, we propose to regress parametric curves w.r.t adaptive axes that help to make more robust predictions towards complex scenes, while in the local vision the structure of lane segment is detected in each of the dynamic anchor cells sampled along the global predicted curves. Moreover, corresponding global and local shape matching losses and anchor cell generation strategies are designed. Experiments on two datasets show that we overwhelm current top methods under high precision standards, and full ablation studies also verify each part of our method. Our codes will be released at https://github.com/Doo-do/FHLD.
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Koehl, Patrice, and Henri Orland. "A Physicist’s View on Partial 3D Shape Matching." Algorithms 16, no. 7 (2023): 346. http://dx.doi.org/10.3390/a16070346.

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A new algorithm is presented to compute nonrigid, possibly partial comparisons of shapes defined by unstructured triangulations of their surfaces. The algorithm takes as input a pair of surfaces with each surface given by a distinct and unrelated triangulation. Its goal is to define a possibly partial correspondence between the vertices of the two triangulations, with a cost associated with this correspondence that can serve as a measure of the similarity of the two shapes. To find this correspondence, the vertices in each triangulation are characterized by a signature vector of features. We tested both the LD-SIFT signatures, based on the concept of spin images, and the wave kernel signatures obtained by solving the Shrödinger equation on the triangulation. A cost matrix C is constructed such that C(k,l) is the norm of the difference of the signature vectors of vertices k and l. The correspondence between the triangulations is then computed as the transport plan that solves the optimal transport or optimal partial transport problem between their sets of vertices. We use a statistical physics approach to solve these problems. The presentation of the proposed algorithm is complemented with examples that illustrate its effectiveness and manageable computing cost.
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13

Bespalov and, Dmitriy, Ali Shokoufandeh, William C. Regli, and Wei Sun. "Scale-Space Representation and Classification of 3D Models." Journal of Computing and Information Science in Engineering 3, no. 4 (2003): 315–24. http://dx.doi.org/10.1115/1.1633576.

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This paper presents a framework for shape matching and classification through scale-space decomposition of 3D models. The algorithm is based on recent developments in efficient hierarchical decomposition of a point distribution in metric space p,d using its spectral properties. Through spectral decomposition, we reduce the problem of matching to that of computing a mapping and distance measure between vertex-labeled rooted trees. We use a dynamic programming scheme to compute distances between trees corresponding to solid models. Empirical evaluation of the algorithm on an extensive set of 3D matching trials demonstrates both robustness and efficiency of the overall approach. Lastly, a technique for comparing shape matchers and classifiers is introduced and the scale-space method is compared with six other known shape matching algorithms.
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14

El Chakik, Abdallah, Abdul Rahman El Sayed, Hassan Alabboud, and Amer Bakkach. "An invariant descriptor map for 3D objects matching." International Journal of Engineering & Technology 9, no. 1 (2020): 59. http://dx.doi.org/10.14419/ijet.v9i1.29918.

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Meshes and point clouds are traditionally used to represent and match 3D shapes. The matching prob-lem can be formulated as finding the best one-to-one correspondence between featured regions of two shapes. This paper presents an efficient and robust 3D matching method using vertices descriptors de-tection to define feature regions and an optimization approach for regions matching. To do so, we compute an invariant shape descriptor map based on 3D surface patches calculated using Zernike coef-ficients. Then, we propose a multi-scale descriptor map to improve the measured descriptor map quali-ty and to deal with noise. In addition, we introduce a linear algorithm for feature regions segmentation according to the descriptor map. Finally, the matching problem is modelled as sub-graph isomorphism problem, which is a combinatorial optimization problem to match feature regions while preserving the geometric. Finally, we show the robustness and stability of our method through many experimental re-sults with respect to scaling, noise, rotation, and translation.
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15

Cao, Dongliang, Paul Roetzer, and Florian Bernard. "Unsupervised Learning of Robust Spectral Shape Matching." ACM Transactions on Graphics 42, no. 4 (2023): 1–15. http://dx.doi.org/10.1145/3592107.

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We propose a novel learning-based approach for robust 3D shape matching. Our method builds upon deep functional maps and can be trained in a fully unsupervised manner. Previous deep functional map methods mainly focus on predicting optimised functional maps alone, and then rely on off-the-shelf post-processing to obtain accurate point-wise maps during inference. However, this two-stage procedure for obtaining point-wise maps often yields sub-optimal performance. In contrast, building upon recent insights about the relation between functional maps and point-wise maps, we propose a novel unsupervised loss to couple the functional maps and point-wise maps, and thereby directly obtain point-wise maps without any post-processing. Our approach obtains accurate correspondences not only for near-isometric shapes, but also for more challenging non-isometric shapes and partial shapes, as well as shapes with different discretisation or topological noise. Using a total of nine diverse datasets, we extensively evaluate the performance and demonstrate that our method substantially outperforms previous state-of-the-art methods, even compared to recent supervised methods. Our code is available at https://github.com/dongliangcao/Unsupervised-Learning-of-Robust-Spectral-Shape-Matching.
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Lee, Jaeho, Joonyoung Park, and Hyunchan Lee. "An algorithm for 3D shape matching using spherical sectioning." Journal of Zhejiang University-SCIENCE A 7, no. 9 (2006): 1508–15. http://dx.doi.org/10.1631/jzus.2006.a1508.

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17

Khan, Mohammad Sharif, Ahmad F. Mohamad Ayob, and Tapabrata Ray. "An efficient memetic algorithm for 3D shape matching problems." Engineering Optimization 46, no. 5 (2013): 687–703. http://dx.doi.org/10.1080/0305215x.2013.795559.

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18

Martinek, Michael, Roberto Grosso, and Günther Greiner. "Interactive partial 3D shape matching with geometric distance optimization." Visual Computer 31, no. 2 (2014): 223–33. http://dx.doi.org/10.1007/s00371-014-1040-4.

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19

Abeysinghe, Sasakthi, Tao Ju, Matthew L. Baker, and Wah Chiu. "Shape modeling and matching in identifying 3D protein structures." Computer-Aided Design 40, no. 6 (2008): 708–20. http://dx.doi.org/10.1016/j.cad.2008.01.013.

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20

Li, Chunyuan, and A. Ben Hamza. "Intrinsic spatial pyramid matching for deformable 3D shape retrieval." International Journal of Multimedia Information Retrieval 2, no. 4 (2013): 261–71. http://dx.doi.org/10.1007/s13735-013-0041-9.

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21

Pan, Bing, Jianhui Zhao, Liang Jia, and Liping Yu. "Smart DIC-3D: towards full-automatic, user-independent, accurate and precise 3D shape and displacement measurement." Measurement Science and Technology 36, no. 3 (2025): 035210. https://doi.org/10.1088/1361-6501/adb5ad.

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Abstract Existing three-dimensional digital image correlation (3D-DIC) for surface 3D shape and deformation measurement requires the users to input key calculation parameters (e.g. subset size) to proceed with stereo and temporal matching. However, the lack of clear guidelines for optimal parameter selection often leads to ambiguity and uncertainty in the final measurements. To eliminate the ambiguity and realize full-automatic, user-independent, accurate and precise 3D-DIC measurements, we present a simple yet effective Smart DIC-3D. By fully considering local speckle quality and deformation, Smart DIC-3D automatically selects the optimal subset size for each calculation point in both stereo and temporal matching. Additionally, a fully automated initial value estimation method, combining speeded-up robust features with a reliability-guided displacement tracking strategy, ensures automatic reliable initial value estimation for both matching processes. Both numerical experiments with simulated stereo speckle images and practical applications including complex shape reconstruction and non-uniform deformation measurement were conducted to verify the effectiveness and accuracy of Smart DIC-3D. The experimental results show that Smart DIC-3D has lower random and under-matched systematic errors than regular 3D-DIC, enabling high-fidelity 3D shape reconstruction and deformation measurement independent of the practitioners’ input.
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Jayadevan, Vijai, Tadamasa Sawada, Edward Delp, and Zygmunt Pizlo. "Perception of 3D Symmetrical and Nearly Symmetrical Shapes." Symmetry 10, no. 8 (2018): 344. http://dx.doi.org/10.3390/sym10080344.

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The human visual system uses priors to convert an ill-posed inverse problem of 3D shape recovery into a well-posed one. In previous studies, we have demonstrated the use of priors like symmetry, compactness and minimal surface in the perception of 3D symmetric shapes. We also showed that binocular perception of symmetric shapes can be well modeled by the above-mentioned priors and binocular depth order information. In this study, which used a shape-matching task, we show that these priors can also be used to model perception of near-symmetrical shapes. Our near-symmetrical shapes are asymmetrical shapes obtained from affine distortions of symmetrical shapes. We found that the perception of symmetrical shapes is closer to veridical than the perception of asymmetrical shapes is. We introduce a metric to measure asymmetry of abstract polyhedral shapes, and a similar metric to measure shape dissimilarity between two polyhedral shapes. We report some key observations obtained by analyzing the data from the experiment. A website was developed with all the shapes used in the experiment, along with the shapes recovered by the subject and the shapes recovered by the model. This website provides a qualitative analysis of the effectiveness of the model and also helps demonstrate the goodness of the shape metric.
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Gao, Yang, Yongjie (Jessica) Zhang, and Prahlad G. Menon. "3D shape comparison of cardiac geometries using a Laplace spectral-shape-matching approach." Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization 4, no. 2 (2015): 86–97. http://dx.doi.org/10.1080/21681163.2015.1057867.

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24

Ng, Seng-Beng, Kok-Why Ng, Rahmita Wirza O. K. Rahmat, and Yih-Jian Yoong. "Blending of three-dimensional geometric model shapes." Indonesian Journal of Electrical Engineering and Computer Science 27, no. 1 (2022): 102–9. https://doi.org/10.11591/ijeecs.v27.i1.pp102-109.

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Three-dimensional (3D) geometric model shapes blending method can create various in-between models from two inputs of models shapes. Though, many blended shapes are implausible due to different inputs of model type, inappropriate matching-parts, improper parts-segmentation, and non-tally number of segmentation parts. are crucial and should be taken into account. The objective of this paper is to study the strengths and weaknesses of some prominent shapes blending methods and the 3D reconstruction methods. An interpolated shape blending program using the Laplacian-based contraction and Slinky-based segmentation method is developed to illustrate the critical problems arise in the shape blending process. Output results are to be compared with some prominent existing methods and one will observe the potential research direction in the blending research work.
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Ogawa, T., and Y. Hori. "COMPARISON WITH ACCURACY OF TERRESTRIAL LASER SCANNER BY USING POINT CLOUD ALIGNED WITH SHAPE MATCHING AND BEST FITTING METHODS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W9 (January 31, 2019): 535–41. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w9-535-2019.

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<p><strong>Abstract.</strong> Recently operation systems of laser scanning have been obviously improved; for instance shape matching has been equipped with software on a post processing stage so measurement without any targets is a prerequisite condition of field surveying with laser scanners. Moreover a shape matching method enables us to easily register a pair of point clouds with some errors even if those data are scanned by several type scanners. Those slightly errors can influence accuracy of alignments if the object is large to require a lot of scans. Laser scanning data has random errors and accuracy of alignments can be improved by matching error distributions of pairs of point clouds to natural distributions. This method is called “best fitting” in contrast “shape matching” in a software, PolyWorks |Inspector. In this paper, accuracy of alignments between shape matching and best fitting is discussed. The scan data of three phaseshift laser scanners (FARO Focus 3D MS120, FARO Focus 3D X330 and Z+F Imager 5016) and two time-of-flight scanners (Leica BLK 360 and Leica Scan station C5) are used for analyses. Accuracy of alignments by using shape matching and best fitting methods is demonstrated by showing points of scan data with histograms of error distributions.</p>
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Lara, López Graciela, Pérez Negrón Adriana Peña, Antonio Angélica de, Jaime Ramírez, and Ricardo Imbert. "Comparative analysis of shape descriptors for 3D objects." Multimedia Tools and Applications 76 (March 1, 2017): 6993–7040. https://doi.org/10.1007/s11042-016-3330-5.

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One of the basic characteristics of an object is its shape. Several research areas in mathematics and computer science have taken an interest in object representation in both 2D images and 3D models, where shape descriptors are a powerful mechanism enabling the processes of classification, retrieval and comparison for object matching. In this paper, we present a literature survey of this broad field, including a comparative analysis based on the above shape descriptor processes. In view of their significance, we identified the shape descriptors implemented using the concept of visual salience. This paper gives an overview of this topic.
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Li, Xin Xin, and Xun Gong. "Building a Standard 3D Face Database Based on Planar Templates." Applied Mechanics and Materials 48-49 (February 2011): 280–83. http://dx.doi.org/10.4028/www.scientific.net/amm.48-49.280.

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This paper presents a new point matching method to solve the dense point-to-point alignment of scanned 3D faces. Texture maps of 3D models are generated at first by unwrapping 3D faces to 2D space. Then, we build planar templates based on the mean shape computed by a group of annotated texture map. 34 landmarks on the unwrapped texture images are located by AAM and the final correspondence is built according to the templates. Comparing to the traditional algorithms, the presented point matching method can achieve good matching accuracy and stability.
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Shao, Tianjia, Weiwei Xu, Kangkang Yin, Jingdong Wang, Kun Zhou, and Baining Guo. "Discriminative Sketch-based 3D Model Retrieval via Robust Shape Matching." Computer Graphics Forum 30, no. 7 (2011): 2011–20. http://dx.doi.org/10.1111/j.1467-8659.2011.02050.x.

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Sun, Han, Xi Xia, and Ligang Liu. "Multi-level Partial Matching Algorithm for Autoscanning of 3D Shape." Journal of Computer-Aided Design & Computer Graphics 31, no. 1 (2019): 10. http://dx.doi.org/10.3724/sp.j.1089.2019.17310.

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Chao, Min-Wen, Chao-Hung Lin, Chih-Chieh Chang, and Tong-Yee Lee. "A graph-based shape matching scheme for 3D articulated objects." Computer Animation and Virtual Worlds 22, no. 2-3 (2011): 295–305. http://dx.doi.org/10.1002/cav.396.

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Dong, Yanzhen, Haitao Wu, Xiao Yang, Xiaobo Chen, and Juntong Xi. "Shape-aware speckle matching network for cross-domain 3D reconstruction." Neurocomputing 585 (June 2024): 127617. http://dx.doi.org/10.1016/j.neucom.2024.127617.

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Han, Li, Shuning Liu, Bing Yu, Shengsi Xu, and Rui Xiang. "Orientation-Preserving Spectral Correspondence for 3D Shape Analysis." Journal of Imaging Science and Technology 64, no. 1 (2020): 10501–1. http://dx.doi.org/10.2352/j.imagingsci.technol.2020.64.1.010501.

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Abstract In this article, the authors present an orientation-preserving spectral correspondence for three-dimensional (3D) shape analysis, which is robust and efficient for topological and deformable changes, even for non-isometric shapes. Our technique introduces an optimal spectral representation by combining the eigendecomposition with principal components analysis (PCA) to the heat kernel Laplacian matrix, and we further propose an efficient symmetry detection method based on so-called dominant eigenfunctions. Finally, a 3D descriptor encoding intrinsic symmetry structure and local geometric feature is constructed which effectively reveals the consistent structure between the deformable shapes. Consequently, sufficient orientation-preserving correspondence can be established in our embedding space. Experimental results showed that our method produces stable matching results in comparison with state-of-the-art methods.
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Feng, Yahong, and Lianpo Wang. "An End-to-end speckle matching network for 3D deformation measurement." Advances in Computer and Engineering Technology Research 1, no. 3 (2024): 46. http://dx.doi.org/10.61935/acetr.3.1.2024.p46.

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Digital image correlation (DIC) is a speckle image-based optical measurement technique for measuring deformation of object. In recent years, deep learning has been widely used in 2D-DIC, while research in the field of 3D-DIC is in its infancy, although 3D-DIC can measure 3D shape and deformation compared to 2D-DIC. 3D-DIC achieves 3D deformation measurement through temporal matching and stereo matching, and it is difficult to perform two matching tasks through an end-to-end network due to the different deformation types of them. To solve this problem, we propose an end-to-end speckle matching network for 3D deformation measurement, called 3D-DICNet. Considering that the difference in deformation types between the two matching tasks is mainly manifested in the deformation scales, we extract the features of different receptive fields, propose a new attention connect volume and multi-scale cost aggregation to achieve the deformation measurements at different scales. Experimental results show that the network can perform 3D deformation measurement with high accuracy and efficiency.
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Nguyen, Mau Tung, Thanh Vu Dang, Minh Kieu Tran Thi, and Pham The Bao. "Generating Point Cloud from Measurements and Shapes Based on Convolutional Neural Network: An Application for Building 3D Human Model." Computational Intelligence and Neuroscience 2019 (September 2, 2019): 1–15. http://dx.doi.org/10.1155/2019/1353601.

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It has been widely known that 3D shape models are comprehensively parameterized using point cloud and meshes. The point cloud particularly is much simpler to handle compared with meshes, and it also contains the shape information of a 3D model. In this paper, we would like to introduce our new method to generating the 3D point cloud from a set of crucial measurements and shapes of importance positions. In order to find the correspondence between shapes and measurements, we introduced a method of representing 3D data called slice structure. A Neural Networks-based hierarchical learning model is presented to be compatible with the data representation. Primary slices are generated by matching the measurements set before the whole point cloud tuned by Convolutional Neural Network. We conducted the experiment on a 3D human dataset which contains 1706 examples. Our results demonstrate the effectiveness of the proposed framework with the average error 7.72% and fine visualization. This study indicates that paying more attention to local features is worthwhile when dealing with 3D shapes.
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Liu, W. C., and B. Wu. "AN INTEGRATED PHOTOGRAMMETRIC AND PHOTOCLINOMETRIC APPROACH FOR PIXEL-RESOLUTION 3D MODELLING OF LUNAR SURFACE." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3 (April 30, 2018): 1117–22. http://dx.doi.org/10.5194/isprs-archives-xlii-3-1117-2018.

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High-resolution 3D modelling of lunar surface is important for lunar scientific research and exploration missions. Photogrammetry is known for 3D mapping and modelling from a pair of stereo images based on dense image matching. However dense matching may fail in poorly textured areas and in situations when the image pair has large illumination differences. As a result, the actual achievable spatial resolution of the 3D model from photogrammetry is limited by the performance of dense image matching. On the other hand, photoclinometry (i.e., shape from shading) is characterised by its ability to recover pixel-wise surface shapes based on image intensity and imaging conditions such as illumination and viewing directions. More robust shape reconstruction through photoclinometry can be achieved by incorporating images acquired under different illumination conditions (i.e., photometric stereo). Introducing photoclinometry into photogrammetric processing can therefore effectively increase the achievable resolution of the mapping result while maintaining its overall accuracy. This research presents an integrated photogrammetric and photoclinometric approach for pixel-resolution 3D modelling of the lunar surface. First, photoclinometry is interacted with stereo image matching to create robust and spatially well distributed dense conjugate points. Then, based on the 3D point cloud derived from photogrammetric processing of the dense conjugate points, photoclinometry is further introduced to derive the 3D positions of the unmatched points and to refine the final point cloud. The approach is able to produce one 3D point for each image pixel within the overlapping area of the stereo pair so that to obtain pixel-resolution 3D models. Experiments using the Lunar Reconnaissance Orbiter Camera - Narrow Angle Camera (LROC NAC) images show the superior performances of the approach compared with traditional photogrammetric technique. The results and findings from this research contribute to optimal exploitation of image information for high-resolution 3D modelling of the lunar surface, which is of significance for the advancement of lunar and planetary mapping.
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36

Ng, Seng-Beng, Kok-Why Ng, Rahmita Wirza O. K. Rahmat, and Yih-Jian Yoong. "Blending of three-dimensional geometric model shapes." Indonesian Journal of Electrical Engineering and Computer Science 27, no. 1 (2022): 102. http://dx.doi.org/10.11591/ijeecs.v27.i1.pp102-109.

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Three-dimensional (3D) geometric model shapes blending method can create various in-between models from two inputs of models shapes. Though, many blended shapes are implausible due to different inputs of model type, inappropriate matching-parts, improper parts-segmentation, and non-tally number of segmentation parts. are crucial and should be taken into account. The objective of this paper is to study the strengths and weaknesses of some prominent shapes blending methods and the 3D reconstruction methods. An interpolated shape blending program using the Laplacian-based contraction and Slinky-based segmentation method is developed to illustrate the critical problems arise in the shape blending process. Output results are to be compared with some prominent existing methods and one will observe the potential research direction in the blending research work
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Xi, Ke, Pengjie Tao, Zhuangqun Niu, et al. "Three-Dimensional Deformation Estimation from Multi-Temporal Real-Scene Models for Landslide Monitoring." Remote Sensing 16, no. 15 (2024): 2705. http://dx.doi.org/10.3390/rs16152705.

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This study proposes a three-dimensional (3D) deformation estimation framework based on the integration of shape and texture information for real-scene 3D model matching, effectively addressing the issue of deformation assessment in large-scale geological landslide areas. By extracting and merging the texture and shape features of matched points, correspondences between points in multi-temporal real-scene 3D models are established, resolving the difficulties faced by existing methods in achieving robust and high-precision 3D point matching over landslide areas. To ensure the complete coverage of the geological disaster area while enhancing computational efficiency during deformation estimation, a voxel-based thinning method to generate interest points is proposed. The effectiveness of the proposed method is validated through tests on a dataset from the Lijie north hill geological landslide area in Gansu Province, China. Experimental results demonstrate that the proposed method significantly outperforms existing classic and advanced methods in terms of matching accuracy metrics, and the accuracy of our deformation estimates is close to the actual measurements obtained from GNSS stations, with an average error of only 2.2 cm.
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38

Kochi, N., T. Sasaki, K. Kitamura, and S. Kaneko. "Robust surface matching by integrating edge segments." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences II-5 (May 28, 2014): 203–10. http://dx.doi.org/10.5194/isprsannals-ii-5-203-2014.

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This paper describes a novel area-based stereo-matching method which aims at reconstructing the shape of objects robustly, correctly, with high precision and with high density. Our goal is to reconstruct correctly the shape of the object by comprising also edges as part of the resulting surface. For this purpose, we need to overcome the problem of how to reconstruct and describe shapes with steep and sharp edges. Area-based matching methods set an image area as a template and search the corresponding match. As a direct consequence of this approach, it becomes not possible to correctly reconstruct the shape around steep edges. Moreover, in the same regions, discontinuities and discrepancies of the shape between the left and right stereo-images increase the difficulties for the matching process. In order to overcome these problems, we propose in this paper the approach of reconstructing the shape of objects by embedding reliable edge line segments into the area-based matching process with parallax estimation. We propose a robust stereo-matching (the extended Edge TIN-LSM) method which integrates edges and which is able to cope with differences in right and left image shape, brightness changes and occlusions. The method consists of the following three steps: (1) parallax estimation, (2) edge-matching, (3) edge-surface matching. In this paper, we describe and explain in detail the process of parallax estimation and the area-based surface-matching with integrated edges; the performance of the proposed method is also validated. The main advantage of this new method is its ability to reconstruct with high precision a 3D model of an object from only two images (for ex. measurement of a tire with 0.14 mm accuracy), thus without the need of a large number of images. For this reason, this approach is intrinsically simple and high-speed.
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39

HU, ZHENCHENG, and KEIICHI UCHIMURA. "SOLUTION OF CAMERA REGISTRATION PROBLEM VIA 3D-2D PARAMETERIZED MODEL MATCHING FOR ON-ROAD NAVIGATION." International Journal of Image and Graphics 04, no. 01 (2004): 3–20. http://dx.doi.org/10.1142/s0219467804001269.

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This paper presents a dynamical solution of camera registration problem for on-road navigation applications via a 3D-2D parameterized model matching algorithm. The traditional camera'fs three dimensional (3D) position and pose estimation algorithms have always employed fixed and known-structure models as well as the depth information to obtain the 3D-2D correlations, which is however unavailable for on-road navigation applications since there are no fixed models in the general road scene. With the constraints of road structure and on-road navigation features, this paper presents a 2D digital road-based road shape modeling algorithm. Dynamically generated multi-lane road shape models are used to match real road scenes to estimate the camera 3D position and pose data. Our algorithms have successfully simplified the 3D-2D correlation problem to the 2D-2D road model matching on the projective image. The algorithms proposed in this paper are validated with the experimental results of real road tests under different conditions and types of road.
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40

Liu, Xiaoyuan, Qinyue Qian, Lingyun Wang, Aijun Wang, and Ming Zhang. "Spatial Inhibition of Return Affected by Self-Prioritization Effect in Three-Dimensional Space." Perception 50, no. 3 (2021): 231–48. http://dx.doi.org/10.1177/0301006621992940.

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Spatial inhibition of return (IOR) being affected by the self-prioritization effect (SPE) in a two-dimensional plane has been well documented. However, it remains unknown how the spatial IOR interacts with the SPE in three-dimensional (3D) space. By constructing a virtual 3D environment, Posner’s classically two-dimensional cue-target paradigm was applied to a 3D space. Participants first associated labels for themselves, their best friends, and strangers with geometric shapes in a shape-label matching task, then performed Experiment 1 (referential information appeared as the cue label) and Experiment 2 (referential information appeared as the target label) to investigate whether the IOR effect could be influenced by the SPE in 3D space. This study showed that when the cue was temporarily established with a self-referential shape and appeared in far space, the IOR effect was the smallest. When the target was temporarily established with a self-referential shape and appeared in near space, the IOR effect disappeared. This study suggests that the IOR effect was affected by the SPE when attention was oriented or reoriented in 3D space and that the IOR effect disappeared or decreased when affected by the SPE in 3D space.
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41

Mueller, M., and T. Voegtle. "DETERMINATION OF STEERING WHEEL ANGLES DURING CAR ALIGNMENT BY IMAGE ANALYSIS METHODS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B5 (June 15, 2016): 77–83. http://dx.doi.org/10.5194/isprs-archives-xli-b5-77-2016.

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Optical systems for automatic visual inspections are of increasing importance in the field of automation in the industrial domain. A new application is the determination of steering wheel angles during wheel track setting of the final inspection of car manufacturing. The camera has to be positioned outside the car to avoid interruptions of the processes and therefore, oblique images of the steering wheel must be acquired. Three different approaches of computer vision are considered in this paper, i.e. a 2D shape-based matching (by means of a plane to plane rectification of the oblique images and detection of a shape model with a particular rotation), a 3D shape-based matching approach (by means of a series of different perspectives of the spatial shape of the steering wheel derived from a CAD design model) and a point-to-point matching (by means of the extraction of significant elements (e.g. multifunctional buttons) of a steering wheel and a pairwise connection of these points to straight lines). The HALCON system (HALCON, 2016) was used for all software developments and necessary adaptions. As reference a mechanical balance with an accuracy of 0.1° was used. The quality assessment was based on two different approaches, a laboratory test and a test during production process. In the laboratory a standard deviation of ±0.035° (2D shape-based matching), ±0.12° (3D approach) and ±0.029° (point-to-point matching) could be obtained. The field test of 291 measurements (27 cars with varying poses and angles of the steering wheel) results in a detection rate of 100% and ±0.48° (2D matching) and ±0.24° (point-to-point matching). Both methods also fulfil the request of real time processing (three measurements per second).
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42

Mueller, M., and T. Voegtle. "DETERMINATION OF STEERING WHEEL ANGLES DURING CAR ALIGNMENT BY IMAGE ANALYSIS METHODS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B5 (June 15, 2016): 77–83. http://dx.doi.org/10.5194/isprsarchives-xli-b5-77-2016.

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Optical systems for automatic visual inspections are of increasing importance in the field of automation in the industrial domain. A new application is the determination of steering wheel angles during wheel track setting of the final inspection of car manufacturing. The camera has to be positioned outside the car to avoid interruptions of the processes and therefore, oblique images of the steering wheel must be acquired. Three different approaches of computer vision are considered in this paper, i.e. a 2D shape-based matching (by means of a plane to plane rectification of the oblique images and detection of a shape model with a particular rotation), a 3D shape-based matching approach (by means of a series of different perspectives of the spatial shape of the steering wheel derived from a CAD design model) and a point-to-point matching (by means of the extraction of significant elements (e.g. multifunctional buttons) of a steering wheel and a pairwise connection of these points to straight lines). The HALCON system (HALCON, 2016) was used for all software developments and necessary adaptions. As reference a mechanical balance with an accuracy of 0.1° was used. The quality assessment was based on two different approaches, a laboratory test and a test during production process. In the laboratory a standard deviation of ±0.035° (2D shape-based matching), ±0.12° (3D approach) and ±0.029° (point-to-point matching) could be obtained. The field test of 291 measurements (27 cars with varying poses and angles of the steering wheel) results in a detection rate of 100% and ±0.48° (2D matching) and ±0.24° (point-to-point matching). Both methods also fulfil the request of real time processing (three measurements per second).
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43

Kim, Min Chul, Hyuk Jin Yoon, Hwi Jeong Chang, and Jong Soo Yoo. "Measurement Accuracy for 3D Structure Shape Change using UAV Images Matching." Journal of Korean Society for Geospatial Information System 25, no. 1 (2017): 47–54. http://dx.doi.org/10.7319/kogsis.2017.25.1.047.

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44

Han, Li, Yuning Tong, Jingyu Piao, et al. "Non Rigid 3D Shape Partial Matching Based on Deep Feature Fusion." Journal of Computer-Aided Design & Computer Graphics 33, no. 3 (2021): 475–86. http://dx.doi.org/10.3724/sp.j.1089.2021.18446.

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45

Zhang Zanzan, 张赞赞, 王辉 Wang Hui, 吴琼 Wu Qiong, and 李志光 Li Zhiguang. "3D Shape Reconstruction Based on Digital Holography of Stereo Matching Techonology." Laser & Optoelectronics Progress 51, no. 11 (2014): 110901. http://dx.doi.org/10.3788/lop51.110901.

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46

Windheuser, Thomas, Ulrich Schlickwei, Frank R. Schimdt, and Daniel Cremers. "Large-Scale Integer Linear Programming for Orientation Preserving 3D Shape Matching." Computer Graphics Forum 30, no. 5 (2011): 1471–80. http://dx.doi.org/10.1111/j.1467-8659.2011.02021.x.

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47

Guo, Qinghua, Yuxi Ruan, Jiangtao Xi, et al. "3D shape measurement of moving object with FFT-based spatial matching." Optics & Laser Technology 100 (March 2018): 325–31. http://dx.doi.org/10.1016/j.optlastec.2017.10.025.

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48

Liu, Yonghuai. "Automatic 3d free form shape matching using the graduated assignment algorithm." Pattern Recognition 38, no. 10 (2005): 1615–31. http://dx.doi.org/10.1016/j.patcog.2005.01.008.

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49

Tabia, Hedi, and Hamid Laga. "Covariance-Based Descriptors for Efficient 3D Shape Matching, Retrieval, and Classification." IEEE Transactions on Multimedia 17, no. 9 (2015): 1591–603. http://dx.doi.org/10.1109/tmm.2015.2457676.

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50

Caelli, Terry, Erol Osman, and Geoff West. "3D Shape Matching and Inspection Using Geometric Features and Relational Learning." Computer Vision and Image Understanding 72, no. 3 (1998): 340–50. http://dx.doi.org/10.1006/cviu.1997.0659.

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