Journal articles: 'Points for 3D reconstruction'

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Ando, Ryuhei, Yuko Ozasa, and Wei Guo. "Robust Surface Reconstruction of Plant Leaves from 3D Point Clouds." Plant Phenomics 2021 (April 2, 2021): 1–15. http://dx.doi.org/10.34133/2021/3184185.

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The automation of plant phenotyping using 3D imaging techniques is indispensable. However, conventional methods for reconstructing the leaf surface from 3D point clouds have a trade-off between the accuracy of leaf surface reconstruction and the method’s robustness against noise and missing points. To mitigate this trade-off, we developed a leaf surface reconstruction method that reduces the effects of noise and missing points while maintaining surface reconstruction accuracy by capturing two components of the leaf (the shape and distortion of that shape) separately using leaf-specific properties. This separation simplifies leaf surface reconstruction compared with conventional methods while increasing the robustness against noise and missing points. To evaluate the proposed method, we reconstructed the leaf surfaces from 3D point clouds of leaves acquired from two crop species (soybean and sugar beet) and compared the results with those of conventional methods. The result showed that the proposed method robustly reconstructed the leaf surfaces, despite the noise and missing points for two different leaf shapes. To evaluate the stability of the leaf surface reconstructions, we also calculated the leaf surface areas for 14 consecutive days of the target leaves. The result derived from the proposed method showed less variation of values and fewer outliers compared with the conventional methods.

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Liang, Shi Guo, Ou Yang Yi, and Hui Wang. "Fast Multi-Layer 3D Reconstruction Algorithm." Advanced Materials Research 267 (June 2011): 827–30. http://dx.doi.org/10.4028/www.scientific.net/amr.267.827.

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A fast multi-layer 3d reconstruction algorithm is proposed to realize 3d body surface layer. Based on multi-layer surface reconstructing the shortest triangle line algorithm are proposed. In order to achieve more rapid reconstruction, a fast multi-layer 3D reconstruction algorithm is proposed. When the points on the layers having some errors, or have some offset, during the reconstruction of layered, it will automatically adjust for each pixel value of the selected layer, so that reconstruction process can be completed faster and more accurately . We give optimization method to realize fast reconstruction under real-time environmental.

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Chen, Sheng Yong, Da Wei Liu, Xiao Yan Wang, Wei Huang, and Qiu Guan. "Complete 3D Modeling from Rotational Devices." Advanced Materials Research 317-319 (August 2011): 843–46. http://dx.doi.org/10.4028/www.scientific.net/amr.317-319.843.

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For acquisition of complete 3D models, this paper uses a rotational device to capture a set of image sequences. A direct projective reconstruction method is proposed by linear transformation, which can avoid getting corresponding points in more than two images. Actually, projective reconstructions are obtained from two neighboring images and the reconstructions are combined with the common 3D points. Finally, all reconstructions are merged into the initial one to construct a complete model. Several practical experiments have been carried out to validate the accuracy of the method.

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Xu, Li, Ling Bai, and Lei Li. "The Effect of 3D Image Virtual Reconstruction Based on Visual Communication." Wireless Communications and Mobile Computing 2022 (January 5, 2022): 1–8. http://dx.doi.org/10.1155/2022/6404493.

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Considering the problems of poor effect, long reconstruction time, large mean square error (MSE), low signal-to-noise ratio (SNR), and structural similarity index (SSIM) of traditional methods in three-dimensional (3D) image virtual reconstruction, the effect of 3D image virtual reconstruction based on visual communication is proposed. Using the distribution set of 3D image visual communication feature points, the feature point components of 3D image virtual reconstruction are obtained. By iterating the 3D image visual communication information, the features of 3D image virtual reconstruction in visual communication are decomposed, and the 3D image visual communication model is constructed. Based on the calculation of the difference of 3D image texture feature points, the spatial position relationship of 3D image feature points after virtual reconstruction is calculated to complete the texture mapping of 3D image. The deep texture feature points of 3D image are extracted. According to the description coefficient of 3D image virtual reconstruction in visual communication, the virtual reconstruction results of 3D image are constrained. The virtual reconstruction algorithm of 3D image is designed to realize the virtual reconstruction of 3D image. The results show that when the number of samples is 200, the virtual reconstruction time of this paper method is 2.1 s, and the system running time is 5 s; the SNR of the virtual reconstruction is 35.5 db. The MSE of 3D image virtual reconstruction is 3%, and the SSIM of virtual reconstruction is 1.38%, which shows that this paper method can effectively improve the ability of 3D image virtual reconstruction.

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Parodi, P., and G. Piccioli. "3D shape reconstruction by using vanishing points." IEEE Transactions on Pattern Analysis and Machine Intelligence 18, no. 2 (1996): 211–17. http://dx.doi.org/10.1109/34.481545.

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Russ, John C. "Automatic vs computer-assisted 3D reconstruction." Proceedings, annual meeting, Electron Microscopy Society of America 50, no. 2 (August 1992): 1050–51. http://dx.doi.org/10.1017/s0424820100129887.

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Images from light or electron microscopy of serial sections must be aligned and corrected for distortion before use in three-dimensional reconstruction. As computer rendering supplants physical modelling, algorithms are desired for automatic alignment and rectification, requiring rotation and rubber-sheeting or warping. A new image can be constructed from each digitized original with polynomial equations relating the pixel coordinates in the new image to those in the original. Interpolation between the pixel values is used to prevent aliasing of edges. Calculating the equation coefficients requires matching points in the serial sections, plus some external or a priori information about the cutting distortion. The difficulties in finding corresponding points suggest that human interaction may be needed to locate the proper matching points, while the computer carries out the more mundane but important tasks of pixel interpolation and rendering.Two approaches to automatic alignment have direct counterparts in the related problem of matching points in stereo pair images.

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Wang, Dejiang, and Huazhen Shu. "Accuracy Analysis of Three-Dimensional Modeling of a Multi-Level UAV without Control Points." Buildings 12, no. 5 (May 3, 2022): 592. http://dx.doi.org/10.3390/buildings12050592.

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Unmanned Aerial Vehicle (UAV) oblique photography technology has been applied more and more widely for the 3D reconstruction of real-scene models due to its high efficiency and low cost. However, there are many kinds of UAVs with different positioning methods, camera models, and resolutions. To evaluate the performance levels of different types of UAVs in terms of their application to 3D reconstruction, this study took a primary school as the research area and obtained image information through oblique photography of four UAVs of different levels at different flight altitudes. We then conducted a comparative analysis of the accuracy of their 3D reconstruction models. The results show that the 3D reconstruction model of M300RTK has the highest dimensional accuracy, with an error of about 1.1–1.4 m per kilometer, followed by M600Pro (1.5–3.6 m), Inspire2 (1.8–4.2 m), and Phantom4Pro (2.4–5.6 m), but the accuracy of the 3D reconstruction model was found to have no relationship with the flight altitude. At the same time, the resolution of the 3D reconstruction model improved as the flight altitude decreased and the image resolution of the PTZ camera increased. The 3D reconstruction model resolution of the M300RTK + P1 camera was the highest. For every 10 m decrease in flight altitude, the clarity of the 3D reconstruction model improved by 16.81%. The UAV flight time decreased as the UAV flying altitude increased, and the time required for 3D reconstruction of the model increased obviously as the number and resolution of photos increased.

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Bournez, E., T. Landes, M. Saudreau, P. Kastendeuch, and G. Najjar. "FROM TLS POINT CLOUDS TO 3D MODELS OF TREES: A COMPARISON OF EXISTING ALGORITHMS FOR 3D TREE RECONSTRUCTION." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W3 (February 23, 2017): 113–20. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w3-113-2017.

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3D models of tree geometry are important for numerous studies, such as for urban planning or agricultural studies. In climatology, tree models can be necessary for simulating the cooling effect of trees by estimating their evapotranspiration. The literature shows that the more accurate the 3D structure of a tree is, the more accurate microclimate models are. This is the reason why, since 2013, we have been developing an algorithm for the reconstruction of trees from terrestrial laser scanner (TLS) data, which we call TreeArchitecture. Meanwhile, new promising algorithms dedicated to tree reconstruction have emerged in the literature. In this paper, we assess the capacity of our algorithm and of two others -PlantScan3D and SimpleTree- to reconstruct the 3D structure of trees. The aim of this reconstruction is to be able to characterize the geometric complexity of trees, with different heights, sizes and shapes of branches. Based on a specific surveying workflow with a TLS, we have acquired dense point clouds of six different urban trees, with specific architectures, before reconstructing them with each algorithm. Finally, qualitative and quantitative assessments of the models are performed using reference tree reconstructions and field measurements. Based on this assessment, the advantages and the limits of every reconstruction algorithm are highlighted. Anyway, very satisfying results can be reached for 3D reconstructions of tree topology as well as of tree volume.

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LIU, HANBO, XIN WANG, and WENYI QIANG. "A FAST METHOD FOR IMPLICIT SURFACE RECONSTRUCTION BASED ON RADIAL BASIS FUNCTIONS NETWORK FROM 3D SCATTERED POINTS." International Journal of Neural Systems 17, no. 06 (December 2007): 459–65. http://dx.doi.org/10.1142/s0129065707001299.

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A method for arbitrary surface reconstruction from 3D large scattered points is proposed in this paper. According to the properties of 3D points, e.g. the non-uniform distribution and unknown topology, an implicit surface model is adopted based on radial basis functions network. And because of the property of locality of radial basis function, the method is fast and robust in surface reconstruction. Furthermore, an adapted K-Means algorithm is used to reduce reconstruction centers. For features completeness, two effective methods are introduced to extract the feature points before the adapted K-Means algorithm. Experiment results show that the presented approach is a good solution for reconstruction from 3D large scattered points.

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HILD, MICHAEL, and KAZUYUKI NISHIJIMA. "RECONSTRUCTION OF 3D SPACE STRUCTURE WITH A ROTATIONAL IMAGING SYSTEM." International Journal of Image and Graphics 02, no. 02 (April 2002): 269–85. http://dx.doi.org/10.1142/s0219467802000615.

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We examine whether the accuracy of 3D space point reconstruction from image pairs can be improved by using rotational imaging. A single camera acquires image pairs at two positions that are separated by a rotation and extracts feature points from both images. Matches of feature point pairs from both images are computed, and then the 3D space coordinates are reconstructed based on the disparity of the matched points. The system carries out optimal rotations to obtain low-error reconstructions, using a specially designed control algorithm. The camera can be rotated 360 degrees around a vertical space axis and approximately 270 degrees around a horizontal space axis. The characteristics of the system are described based on simulations and it is shown, through experiments with a prototype, that this system has low matching error, and can cope with occlusions and periodic image structure. The system is adequate for reconstruction of static scenes.

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Latief, Mohammad Adhitya. "THE ROLE OF 3D MODEL AS SURGICAL GUIDANCE IN MANDIBULAR RECONSTRUCTION SURGERY." Jurnal Ilmiah dan Teknologi Kedokteran Gigi 16, no. 2 (February 23, 2021): 79–85. http://dx.doi.org/10.32509/jitekgi.v16i2.1079.

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reconstruction surgery is a challenging surgery that require well prepared presurgical plan to minimize the risk of failure, to accommodate the need for precision preoperative planning, surgeons frequently need guidance such as a3-dimensional (3D) model to display complex cranial structures. Evaluation of the 3D model as surgical guidance require a review measurement regarding its efficiency and pitfalls. Purpose: the purpose of this research is to understand the importants key points that will resulted succesfull reconstructive surgery using 3D model as surgical guidance. Method: the evaluation of surgical result in mandibular reconstruction surgery from our Department Oral and Maxillofacial surgery, Universitas Indonesia from 2012 to 2017 reveal the differences. We analyze several keypoints that may affect to the succesfull of reconstruction surgery result. Result: we compared the result between years before and after 2015, this is where we start obligate all reconstruction surgery need to have preoperative planning using3D Model. Several keypoints in using 3D model is acknowledgeable. Conclusion: the use of 3D models as surgical guidance has important role to minimize post reconstructive surgery result, surgeon need to understand the principal and keypoints in preoperative planning and regarding the use of 3D model.

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Xiong, Zi Ming, and Gang Wan. "An Approach to Automatic Great-Scene 3D Reconstruction Based on UAV Sequence Images." Applied Mechanics and Materials 229-231 (November 2012): 2294–97. http://dx.doi.org/10.4028/www.scientific.net/amm.229-231.2294.

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In this paper, we propose an approach to automatic great-scene 3D reconstruction based on UAV sequence images. In this method, Harris feature point and SIFT feature vector is used to distill image feature, achieving images match; quasi-perspective projection model and factorization is employed to calibrate the uncalibrated image sequences automatically; Efficient suboptimal solutions to the optimal triangulation is plied to obtain the coordinate of 3D points; quasi-dense diffusing algorithm is bestowed to make 3D point denseness; the algorithm of bundle adjustment is taken to improve the precision of 3D points; the approach of Possion surface reconstruction is used to make 3D points gridded. This paper introduces the theory and technology of computer vision into great-scene 3D reconstruction, provides a new way for the construction of 3D scene, and provides a new thinking for the appliance of UAV sequence images.

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Yan, J., N. Grasso, S. Zlatanova, R. C. Braggaar, and D. B. Marx. "CHALLENGES IN FLYING QUADROTOR UNMANNED AERIAL VEHICLE FOR 3D INDOOR RECONSTRUCTION." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W7 (September 12, 2017): 423–30. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w7-423-2017.

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Three-dimensional modelling plays a vital role in indoor 3D tracking, navigation, guidance and emergency evacuation. Reconstruction of indoor 3D models is still problematic, in part, because indoor spaces provide challenges less-documented than their outdoor counterparts. Challenges include obstacles curtailing image and point cloud capture, restricted accessibility and a wide array of indoor objects, each with unique semantics. Reconstruction of indoor environments can be achieved through a photogrammetric approach, e.g. by using image frames, aligned using recurring corresponding image points (CIP) to build coloured point clouds. Our experiments were conducted by flying a QUAV in three indoor environments and later reconstructing 3D models which were analysed under different conditions. Point clouds and meshes were created using Agisoft PhotoScan Professional. We concentrated on flight paths from two vantage points: 1) safety and security while flying indoors and 2) data collection needed for reconstruction of 3D models. We surmised that the main challenges in providing safe flight paths are related to the physical configuration of indoor environments, privacy issues, the presence of people and light conditions. We observed that the quality of recorded video used for 3D reconstruction has a high dependency on surface materials, wall textures and object types being reconstructed. Our results show that 3D indoor reconstruction predicated on video capture using a QUAV is indeed feasible, but close attention should be paid to flight paths and conditions ultimately influencing the quality of 3D models. Moreover, it should be decided in advance which objects need to be reconstructed, e.g. bare rooms or detailed furniture.

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Chen, Huihong, and Shiming Li. "Simulation of 3D Image Reconstruction in Rigid body Motion." MATEC Web of Conferences 232 (2018): 02002. http://dx.doi.org/10.1051/matecconf/201823202002.

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3D image reconstruction under rigid body motion is affected by rigid body motion and visual displacement factors, which leads to low quality of 3D image reconstruction and more noise, in order to improve the quality of 3D image reconstruction of rigid body motion. A 3D image reconstruction technique is proposed based on corner detection and edge contour feature extraction in this paper. Region scanning and point scanning are combined to scan rigid body moving object image. The wavelet denoising method is used to reduce the noise of the 3D image. The edge contour feature of the image is extracted. The sparse edge pixel fusion method is used to decompose the feature of the 3D image under the rigid body motion. The irregular triangulation method is used to extract and reconstruct the information features of the rigid body 3D images. The reconstructed feature points are accurately calibrated with the corner detection method to realize the effective reconstruction of the 3D images. The simulation results show that the method has good quality, high SNR of output image and high registration rate of feature points of image reconstruction, and proposed method has good performance of 3D image reconstruction.

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Yang, Xuyuan, and Guang Jiang. "A Practical 3D Reconstruction Method for Weak Texture Scenes." Remote Sensing 13, no. 16 (August 6, 2021): 3103. http://dx.doi.org/10.3390/rs13163103.

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In recent years, there has been a growing demand for 3D reconstructions of tunnel pits, underground pipe networks, and building interiors. For such scenarios, weak textures, repeated textures, or even no textures are common. To reconstruct these scenes, we propose covering the lighting sources with films of spark patterns to “add” textures to the scenes. We use a calibrated camera to take pictures from multiple views and then utilize structure from motion (SFM) and multi-view stereo (MVS) algorithms to carry out a high-precision 3D reconstruction. To improve the effectiveness of our reconstruction, we combine deep learning algorithms with traditional methods to extract and match feature points. Our experiments have verified the feasibility and efficiency of the proposed method.

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Li, Na, Jiquan Yang, Aiqing Guo, Yijian Liu, and Hai Liu. "Triangulation Reconstruction for 3D Surface Based on Information Model." Cybernetics and Information Technologies 16, no. 5 (October 1, 2016): 27–33. http://dx.doi.org/10.1515/cait-2016-0049.

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Abstract The aim of this paper is to address the surface reconstruction from point cloud in reverser engineering. The data was acquired through a 3D scan device and was processed as point cloud data. The points in cloud were connected to build 3D surface. The points cloud was processed in four steps to get 3D information surface. First, the subtraction scheme was used to get cover boxes ended with the set of convex was found under the convergence rule. Secondly, the points in the box were projected to the directions which were close to the normal direction method. Thirdly the overlap was avoided by using convergence rule and inner subdivision rule. Finally the information model was used to reconstruction. The method was used in landslide monitoring of Three Gorges area for 3D surface reconstruction and monitoring. The reconstruction method obtains high precision and low complexity. It is effective for large scale monitoring.

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Zhang, Tian, Jian Hua Liu, Cheng Tong Tang, and Shao Li Liu. "3D Reconstruction Method of Bent Tube with NURBS Curve." Applied Mechanics and Materials 300-301 (February 2013): 112–18. http://dx.doi.org/10.4028/www.scientific.net/amm.300-301.112.

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To solve the difficulty and low efficiency of three-dimensional reconstruction of complex spatial form bent tube, a stereo vision method with NURBS curve to achieve three-dimensional reconstruction of bent tube is presented. This method first extracts central axis and the edge line of bent tube by the grayscale image, and the outer diameter of bent tube is calculated through the edge line extracted. On the premise of affine camera model, NURBS curve has been chosen as the primitive of reconstruction, and by using its affine invariance, according to the principle of binocular vision, the central axis of bent tube is reconstructed through reconstructing the control points. Finally, the three-dimensional model of bent tube is reconstructed by three-dimensional modeling technique. Experimental results show that, relative to the traditional methods, this method makes a big improvement on the efficiency and accuracy of three-dimensional reconstruction of bent tube.

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Navaneet, K. L., Priyanka Mandikal, Mayank Agarwal, and R. Venkatesh Babu. "CAPNet: Continuous Approximation Projection for 3D Point Cloud Reconstruction Using 2D Supervision." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 8819–26. http://dx.doi.org/10.1609/aaai.v33i01.33018819.

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Knowledge of 3D properties of objects is a necessity in order to build effective computer vision systems. However, lack of large scale 3D datasets can be a major constraint for datadriven approaches in learning such properties. We consider the task of single image 3D point cloud reconstruction, and aim to utilize multiple foreground masks as our supervisory data to alleviate the need for large scale 3D datasets. A novel differentiable projection module, called ‘CAPNet’, is introduced to obtain such 2D masks from a predicted 3D point cloud. The key idea is to model the projections as a continuous approximation of the points in the point cloud. To overcome the challenges of sparse projection maps, we propose a loss formulation termed ‘affinity loss’ to generate outlierfree reconstructions. We significantly outperform the existing projection based approaches on a large-scale synthetic dataset. We show the utility and generalizability of such a 2D supervised approach through experiments on a real-world dataset, where lack of 3D data can be a serious concern. To further enhance the reconstructions, we also propose a test stage optimization procedure to obtain reconstructions that display high correspondence with the observed input image.

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Xiao, Longdong, Chong Li, Yue Cai, Mingxing Zhou, Tao Zhou, Xueyan Gao, Huaqiang Du, Yufeng Zhou, and Guomo Zhou. "Preliminary Application of Ground-Penetrating Radar for Reconstruction of Root System Architecture in Moso Bamboo." Remote Sensing 13, no. 14 (July 17, 2021): 2816. http://dx.doi.org/10.3390/rs13142816.

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Root system architecture (RSA) refers to the geometric features and topology of the root system. Ground-penetrating radar (GPR) is a possible method of RSA reconstruction. However, because the topology of the root system is not directly accessible by GPR, GPR-based reconstruction must be complemented by manual connection of root points, resulting in limited accuracy. In this study, we used both GPR and direct excavation to obtain 3D coordinates (XYZ coordinates) and diameters of moso bamboo rhizomes on an orthogonal grid. A score function for selecting the best-connected root points was developed using rhizome diameter, depth, extension angle, and measured line spacing, which was then used to recover the topology of discrete root points. Based on the recovered topology, the 3D RSA of the rhizomes was reconstructed using a smoothing function. Based on the excavation data, the reconstructed RSA was generally consistent with the measured RSA, with 78.13% of root points correctly connected. The reconstructed RSA based on GPR data thus provided a rough approximation of the measured RSA, with errors arising due to missing root points and rhizome displacement. The proposed algorithm for reconstructing 3D RSA further enriches the application of ground-penetrating radar to root detection.

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Li, Tianping, Hongxin Xu, Hua Zhang, and Honglin Wan. "Detail 3D Face Reconstruction Based on 3DMM and Displacement Map." Journal of Sensors 2021 (June 25, 2021): 1–13. http://dx.doi.org/10.1155/2021/9921101.

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How to accurately reconstruct the 3D model human face is a challenge issue in the computer vision. Due to the complexity of face reconstruction and diversity of face features, most existing methods are aimed at reconstructing a smooth face model with ignoring face details. In this paper a novel deep learning-based face reconstruction method is proposed. It contains two modules: initial face reconstruction and face details synthesis. In the initial face reconstruction module, a neural network is used to detect the facial feature points and the angle of the pose face, and 3D Morphable Model (3DMM) is used to reconstruct the rough shape of the face model. In the face detail synthesis module, Conditional Generation Adversarial Network (CGAN) is used to synthesize the displacement map. The map provides texture features to render to the face surface reconstruction, so as to reflect the face details. Our proposal is evaluated by Facescape dataset in experiments and achieved better performance than other current methods.

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Liu, Zhong Yan, Guo Quan Wang, and Dong Ping Wang. "A 3D Reconstruction Method Based on Binocular View Geometry." Applied Mechanics and Materials 33 (October 2010): 299–303. http://dx.doi.org/10.4028/www.scientific.net/amm.33.299.

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A method was proposed to gain three-dimensional (3D) reconstruction based on binocular view geometry. Images used to calibrate cameras and reconstruct car’s rearview mirror by image acquisition system, by calibration image, a camera's intrinsic and extrinsic parameters, projective and fundamental matrixes were drawn by Matlab7.1;the collected rearview mirror images is pretreated to draw refined laser, extracted feature points, find the very appropriate match points by epipolar geometry principle; according to the camera imaging model to calculate the coordinates of space points, display point cloud, fitting space points to reconstruct car’s rearview mirror; experimental results show this method can better restore the car’s rearview mirror of 3D information.

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Apollonio, F. I., A. Ballabeni, M. Gaiani, and F. Remondino. "Evaluation of feature-based methods for automated network orientation." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-5 (June 5, 2014): 47–54. http://dx.doi.org/10.5194/isprsarchives-xl-5-47-2014.

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Every day new tools and algorithms for automated image processing and 3D reconstruction purposes become available, giving the possibility to process large networks of unoriented and markerless images, delivering sparse 3D point clouds at reasonable processing time. In this paper we evaluate some feature-based methods used to automatically extract the tie points necessary for calibration and orientation procedures, in order to better understand their performances for 3D reconstruction purposes. The performed tests – based on the analysis of the SIFT algorithm and its most used variants – processed some datasets and analysed various interesting parameters and outcomes (e.g. number of oriented cameras, average rays per 3D points, average intersection angles per 3D points, theoretical precision of the computed 3D object coordinates, etc.).

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Wang, Xiao Hui. "Virtual Simulation of Aerobics Movement Based on Vision." Advanced Materials Research 989-994 (July 2014): 1997–2000. http://dx.doi.org/10.4028/www.scientific.net/amr.989-994.1997.

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In aerobics, the motion state randomness of key feature points is great, so it is difficult to establish an accurate dynamic model for sports' shape base. Traditional 3D reconstruction algorithms use fixes shape base which hardly expresses the change parameters of complex movement and motion law of large-scale dynamic features, thereby leading to non-realistic reconstruction results. The paper proposes a new reconstruction algorithm for aerobics 3D motion images that corrects the neighborhood system of feature points by motion parameters until the parameter is stable to ensure accuracy and the stability of correction. The simulation results show that, the proposed algorithm avoids drawbacks of sports reconstruction results caused by the great randomness of aerobics' motion state, thereby complete 3D reconstruction for aerobics' motion images.

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Song, Jun. "A New Surface Reconstruction Algorithm for Noisy 3D Unorganized Points." Applied Mechanics and Materials 217-219 (November 2012): 1312–17. http://dx.doi.org/10.4028/www.scientific.net/amm.217-219.1312.

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This paper puts forward a new method of surface reconstruction. Power crust algorithm can reconstruct a good surface that is topological valid and be proved theoretically. But when the point cloud is noisy, the surface reconstructed is not good and its running time is long. This paper proposes a improved method of fuzzy c-means clustering to delete the noisy points and a non-uniformly sampling method to resample the input data set according to the local feature size before reconstruction. Experimental results show that the efficiency of the algorithm has been improved much more.

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XIAO, YIJUN, MINGYUE DING, and JIAXIONG PENG. "B-SPLINE BASED STEREO FOR 3D RECONSTRUCTION OF LINE-LIKE OBJECTS USING AFFINE CAMERA MODEL." International Journal of Pattern Recognition and Artificial Intelligence 15, no. 02 (March 2001): 347–58. http://dx.doi.org/10.1142/s0218001401000915.

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This paper presents a novel curve based algorithm of stereo vision to reconstruct 3D line-like objects. B-spline approximations of 2D edge curves are selected as primitives for the reconstruction of their corresponding space curves so that, under the assumption of affine camera model, a 3D curve can be derived from reconstructing its control points according to the affine invariant property of B-Spline curves. The superiority of B-spline model in representing free-form curves gives good geometric properties of reconstruction results. Both theoretical analysis and experimental results demonstrate the validity of our approach.

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Zhang, Ning, and YongJia Zhao. "3D recognition based on ordered images reconstruction." MATEC Web of Conferences 232 (2018): 02045. http://dx.doi.org/10.1051/matecconf/201823202045.

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Nowadays, more and more applications require precise and quickly 3D recognition, such as augmented reality and robot navigation. In recent years, model-based methods can get accurate object or scene recognition, but it takes a lot of time to reconstruct the model. Therefore, we propose a fast 3D reconstruction method based on ordered images for robust and accurate 3D recognition. The proposed algorithm consists of two parts, the offline processing stage, and the online processing stage. First, in the offline processing stage, the sparse point cloud model of the scene or object is reconstructed based on the sequential images, optimized using the BA algorithm based on the local correlation frame, and then the local descriptor of the resulting model points is stored. Secondly, in the online processing stage, for each image frame of the camera video, a matching relationship between the stored point cloud and the 2D feature points on the image frame is established, based on which the pose of the camera can be solved accurately.

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He, Wei. "Research on Outdoor Garden Scene Reconstruction Based on PMVS Algorithm." Scientific Programming 2021 (November 24, 2021): 1–10. http://dx.doi.org/10.1155/2021/4491382.

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The three-dimensional reconstruction of outdoor landscape is of great significance for the construction of digital city. With the rapid development of big data and Internet of things technology, when using the traditional image-based 3D reconstruction method to restore the 3D information of objects in the image, there will be a large number of redundant points in the point cloud and the density of the point cloud is insufficient. Based on the analysis of the existing three-dimensional reconstruction technology, combined with the characteristics of outdoor garden scene, this paper gives the detection and extraction methods of relevant feature points and adopts feature matching and repairing the holes generated by point cloud meshing. By adopting the candidate strategy of feature points and adding the mesh subdivision processing method, an improved PMVS algorithm is proposed and the problem of sparse point cloud in 3D reconstruction is solved. Experimental results show that the proposed method not only effectively realizes the three-dimensional reconstruction of outdoor garden scene, but also improves the execution efficiency of the algorithm on the premise of ensuring the reconstruction effect.

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de Jesus, Kelly, Karla de Jesus, Pedro Figueiredo, João Paulo Vilas-Boas, Ricardo Jorge Fernandes, and Leandro José Machado. "Reconstruction Accuracy Assessment of Surface and Underwater 3D Motion Analysis: A New Approach." Computational and Mathematical Methods in Medicine 2015 (2015): 1–8. http://dx.doi.org/10.1155/2015/269264.

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This study assessed accuracy of surface and underwater 3D reconstruction of a calibration volume with and without homography. A calibration volume (6000 × 2000 × 2500 mm) with 236 markers (64 above and 88 underwater control points—with 8 common points at water surface—and 92 validation points) was positioned on a 25 m swimming pool and recorded with two surface and four underwater cameras. Planar homography estimation for each calibration plane was computed to perform image rectification. Direct linear transformation algorithm for 3D reconstruction was applied, using 1600000 different combinations of 32 and 44 points out of the 64 and 88 control points for surface and underwater markers (resp.). Root Mean Square (RMS) error with homography of control and validations points was lower than without it for surface and underwater cameras (P≤0.03). With homography, RMS errors of control and validation points were similar between surface and underwater cameras (P≥0.47). Without homography, RMS error of control points was greater for underwater than surface cameras (P≤0.04) and the opposite was observed for validation points (P≤0.04). It is recommended that future studies using 3D reconstruction should include homography to improve swimming movement analysis accuracy.

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Zhong, Lijun, Junyou Qin, Xia Yang, Xiaohu Zhang, Yang Shang, Hongliang Zhang, and Qifeng Yu. "An Accurate Linear Method for 3D Line Reconstruction for Binocular or Multiple View Stereo Vision." Sensors 21, no. 2 (January 19, 2021): 658. http://dx.doi.org/10.3390/s21020658.

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For the problem of 3D line reconstruction in binocular or multiple view stereo vision, when there are no corresponding points on the line, the method called Direction-then-Point (DtP) can be used, and if there are two pairs of corresponding points on the line, the method called Two Points 3D coordinates (TPS) can be used. However, when there is only one pair of corresponding points on the line, can we get the better accuracy than DtP for 3D line reconstruction? In this paper, a linear and more accurate method called Point-then-Direction (PtD) is proposed. First, we used the intersection method to obtain the 3D point’s coordinate from its corresponding image points. Then, we used this point as a position on the line to calculate the direction of the line by minimizing the image angle residual. PtD is also suitable for multiple camera systems. The simulation results demonstrate that PtD increases the accuracy of both the direction and the position of the 3D line compared to DtP. At the same time, PtD achieves a better result in direction of the 3D line than TPS, but has a lower accuracy in the position of 3D lines than TPS.

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Hou, Zhen Jie, and Li Guo Gu. "Triangulation Based on 3D Reconstruction Technique." Applied Mechanics and Materials 121-126 (October 2011): 4249–53. http://dx.doi.org/10.4028/www.scientific.net/amm.121-126.4249.

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For decades of research on triangulation, Scattered surface area triangulation has achieved some results, but a lot of algorithms extended to three-dimensional space still have some problems.In this paper I analyzes the existing algorithms and propose a idea based on the Combination of the incremental method and divide algorithm ,which directly realize the triangulation of scattered points in space. Through the triangulation of space scattered point ,it's result eventually meet the triangular mesh model of the reconstruction and the mesh is very uniform. The model reproduce the object model intuitively and clearly. This study provide meaning of the reference and guide in such a work

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Soheilian, B., and M. Brédif. "Multi-view 3D circular target reconstruction with uncertainty analysis." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences II-3 (August 7, 2014): 143–48. http://dx.doi.org/10.5194/isprsannals-ii-3-143-2014.

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The paper presents an algorithm for reconstruction of 3D circle from its apparition in n images. It supposes that camera poses are known up to an uncertainty. They will be considered as observations and will be refined during the reconstruction process. First, circle apparitions will be estimated in every individual image from a set of 2D points using a constrained optimization. Uncertainty of 2D points are propagated in 2D ellipse estimation and leads to covariance matrix of ellipse parameters. In 3D reconstruction process ellipse and camera pose parameters are considered as observations with known covariances. A minimal parametrization of 3D circle enables to model the projection of circle in image without any constraint. The reconstruction is performed by minimizing the length of observation residuals vector in a non linear Gauss-Helmert model. The output consists in parameters of the corresponding circle in 3D and their covariances. The results are presented on simulated data.

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Matsumoto, H., Y. Mori, and H. Masuda. "EXTRACTION AND SHAPE RECONSTRUCTION OF GUARDRAILS USING MOBILE MAPPING DATA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W13 (June 5, 2019): 1061–68. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w13-1061-2019.

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Abstract. The mobile mapping system (MMS) can acquire dense point-clouds of roads and roadside features. Roads are often separated into roadways and walkways in many urban areas. Since guardrails are installed to separate roadways and sidewalks, it is important to detect guardrails from point-clouds and reconstruct their 3D models for 3D street maps. Since there are a large variety of designs for guardrails in Japan, flexible methods are required for detection and reconstruction of guardrails. In this paper, we propose a new method for extracting guardrails from point-clouds, and reconstructing their 3D models. Since the MMS captures point-clouds and camera images synchronously, guardrails are detected using both point-clouds and images. In our method, point-clouds are segmented into small segments, and corresponding images are cropped from camera images. Then cropped images are classified into two classes of guardrails and others using the convolutional neural network. When guardrail points are obtained, 3D models of guardrails are reconstructed. However, point-clouds of guardrails are too sparse to reconstruct 3D shapes when guardrails consist of thin pipes. Since the same unit shape repeatedly appears in a guardrail, we create dense point-clouds by superimposing points of unit shapes. Then we reconstruct 3D shapes of pipes, beams, and poles of guardrails. In our evaluation using point-clouds in urban areas, our method could achieve good results of extraction and shape reconstruction of guardrails.

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Tian, Cheng Jun, Zhi Yong An, Li Juan Li, and Bing Gao He. "Three Dimensional Reconstruction System Based on Laser Radar." Advanced Materials Research 102-104 (March 2010): 145–49. http://dx.doi.org/10.4028/www.scientific.net/amr.102-104.145.

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With the development of manufacturing, obtaining 3D data of objects surface effectively and precisely has been important. In this paper, laser radar is selected to gain 3D geometric data by comparing the current digital measurement techniques, and the measurement principle of laser radar is discussed in detail. For obtaining the whole surface points cloud of work piece and reducing the error of station moving, the mathematical model of station moving is established. This paper also analyzes the characteristics of points cloud data collected using laser radar, estimates the normals of scattered points with PCA method. Finally, the 3D surface of work piece is reconstructed using radial basis function interpolation.This system has the advantages of fast measurement speed, large measurement range and high degree automation.Because laser radar uses optical non-contact measurement mode, so there are no special requirements of the object surface.

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Lei, Ziang. "A Poisson Equation-Based Method for 3D Reconstruction of Animated Images." Advances in Mathematical Physics 2021 (November 27, 2021): 1–11. http://dx.doi.org/10.1155/2021/1547630.

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3D reconstruction techniques for animated images and animation techniques for faces are important research in computer graphics-related fields. Traditional 3D reconstruction techniques for animated images mainly rely on expensive 3D scanning equipment and a lot of time-consuming postprocessing manually and require the scanned animated subject to remain in a fixed pose for a considerable period. In recent years, the development of large-scale computing power of computer-related hardware, especially distributed computing, has made it possible to come up with a real-time and efficient solution. In this paper, we propose a 3D reconstruction method for multivisual animated images based on Poisson’s equation theory. The calibration theory is used to calibrate the multivisual animated images, obtain the internal and external parameters of the camera calibration module, extract the feature points from the animated images of each viewpoint by using the corner point detection operator, then match and correct the extracted feature points by using the least square median method, and complete the 3D reconstruction of the multivisual animated images. The experimental results show that the proposed method can obtain the 3D reconstruction results of multivisual animation images quickly and accurately and has certain real-time and reliability.

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Yang, Zhi Yuan. "A Reconstruction Model for 3D Human Motion Based on Images Processing." Applied Mechanics and Materials 556-562 (May 2014): 5021–23. http://dx.doi.org/10.4028/www.scientific.net/amm.556-562.5021.

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Traditional 3D reconstruction algorithms use fixes shape base which hardly expresses the change parameters of complex movement and motion law of large-scale dynamic features, thereby leading to non-realistic reconstruction results. The paper proposes a new reconstruction algorithm for 3D motion images that corrects the neighborhood system of feature points by motion parameters and reasons number base K to ensure accuracy. The simulation results show that, the proposed algorithm avoids drawbacks of sports reconstruction results caused by the great randomness of motion state, thereby complete 3D motion images' reconstruction.

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Chen, Zhong, Zhiwei Hou, Mujian Xia, and Yuegang Xing. "Adaptive Surface Mesh Reconstruction for Computed Tomography Images." Journal of Medical Imaging and Health Informatics 9, no. 6 (August 1, 2019): 1086–94. http://dx.doi.org/10.1166/jmihi.2019.2710.

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In medical applications, it is important to reconstruct surface meshes from Computed Tomography (CT) images. Surface mesh reconstruction of biological tissues actually suffers from staircase artifacts, due to anisotropic CT data. To solve this problem, this paper proposes an adaptive surface mesh reconstruction method. We convert the contour pixels of medical image to contour points and exploit the adaptive spherical cover to produce an approximating surface based on the contour points. Due to the reconstruction quality depending on the accurate normal estimation, computing the normal vectors from the negative gradient based on 3D binary volume data instead of classical principal component analysis (PCA), and then covering contour points by adaptive spheres, linking the auxiliary points in the spheres for reconstructing adaptive triangular meshes. The presented method has been used in CT images of the first cervical vertebrae (C1), scapula, as well as the third lumbar vertebrae (L3) and the results are analyzed regarding their smoothness, accuracy and mesh quality. The results show that our method can reconstruct smooth, accurate and high-quality adaptive surface meshes.

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Jiang, Ze Tao, Qing Hui Xiao, and Ling Hong Zhu. "3D Reconstruction Based on Hexagonal Pixel’s Dense Stereo Matching." Applied Mechanics and Materials 20-23 (January 2010): 487–92. http://dx.doi.org/10.4028/www.scientific.net/amm.20-23.487.

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A new feature points extraction method is presented, which consider pixel as hexagonal. The method quasi increases the density of image pixel, expands the dynamic range of feature point extraction, increases the number of the features and resolves the problem of deformation of reconstruction which was leaded by lack of feature points. Firstly, the method was successful applied to sift operator of features extraction in this paper and then use dense stereo matching method to find the matching point of the image sequences. Secondly, through the RANSAC method to eliminate mistake matches, and by the camera matrix, calculate the corresponding points’ three-dimensional coordinates of space. Finally, the 3D model can be established through the partition merging triangulation method and texture mapping. Experimental results show that this method can get more accurate matches pairs and achieve a satisfactory effect of 3D reconstruction.

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Guo, Zhenmin. "Adaptive method for weldment surface reconstruction to scattered 3D points." Chinese Journal of Mechanical Engineering (English Edition) 15, supp (2002): 64. http://dx.doi.org/10.3901/cjme.2002.supp.064.

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Zhao, Jianhui, Ling Li, and Kwoh Chee Keong. "3D Posture Reconstruction and Human Animation from 2D Feature Points." Computer Graphics Forum 24, no. 4 (December 2005): 759–71. http://dx.doi.org/10.1111/j.1467-8659.2005.00900.x.

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Abratenko, P., R. An, J. Anthony, L. Arellano, J. Asaadi, A. Ashkenazi, S. Balasubramanian, et al. "Wire-cell 3D pattern recognition techniques for neutrino event reconstruction in large LArTPCs: algorithm description and quantitative evaluation with MicroBooNE simulation." Journal of Instrumentation 17, no. 01 (January 1, 2022): P01037. http://dx.doi.org/10.1088/1748-0221/17/01/p01037.

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Abstract Wire-Cell is a 3D event reconstruction package for liquid argon time projection chambers. Through geometry, time, and drifted charge from multiple readout wire planes, 3D space points with associated charge are reconstructed prior to the pattern recognition stage. Pattern recognition techniques, including track trajectory and dQ/dx (ionization charge per unit length) fitting, 3D neutrino vertex fitting, track and shower separation, particle-level clustering, and particle identification are then applied on these 3D space points as well as the original 2D projection measurements. A deep neural network is developed to enhance the reconstruction of the neutrino interaction vertex. Compared to traditional algorithms, the deep neural network boosts the vertex efficiency by a relative 30% for charged-current νe interactions. This pattern recognition achieves 80–90% reconstruction efficiencies for primary leptons, after a 65.8% (72.9%) vertex efficiency for charged-current νe (νμ) interactions. Based on the resulting reconstructed particles and their kinematics, we also achieve 15-20% energy reconstruction resolutions for charged-current neutrino interactions.

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Siswantoro, Joko, Anton Satria Prabuwono, Azizi Abdullah, and Bahari Idrus. "Monte Carlo Method with Heuristic Adjustment for Irregularly Shaped Food Product Volume Measurement." Scientific World Journal 2014 (2014): 1–10. http://dx.doi.org/10.1155/2014/683048.

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Volume measurement plays an important role in the production and processing of food products. Various methods have been proposed to measure the volume of food products with irregular shapes based on 3D reconstruction. However, 3D reconstruction comes with a high-priced computational cost. Furthermore, some of the volume measurement methods based on 3D reconstruction have a low accuracy. Another method for measuring volume of objects uses Monte Carlo method. Monte Carlo method performs volume measurements using random points. Monte Carlo method only requires information regarding whether random points fall inside or outside an object and does not require a 3D reconstruction. This paper proposes volume measurement using a computer vision system for irregularly shaped food products without 3D reconstruction based on Monte Carlo method with heuristic adjustment. Five images of food product were captured using five cameras and processed to produce binary images. Monte Carlo integration with heuristic adjustment was performed to measure the volume based on the information extracted from binary images. The experimental results show that the proposed method provided high accuracy and precision compared to the water displacement method. In addition, the proposed method is more accurate and faster than the space carving method.

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JIN, CHENG. "GEOMETRIC INVARIANTS CONSTRUCTION FROM MULTIPLE VIEWS." International Journal of Modeling, Simulation, and Scientific Computing 02, no. 02 (June 2011): 195–206. http://dx.doi.org/10.1142/s1793962311000402.

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Geometric invariants have wide applications in computer vision and their precision has long been a hot topic. In most of the existing methods, three-dimensional (3D) invariants have been obtained by reconstruction of the object structure, where fundamental matrices between image pairs should be first established. Consequently, there are additional errors introduced during invariants construction and could be very time consuming. In this paper, a novel algorithm to calculate 3D projective invariants from multiple images has been proposed, without reconstructing the object structures explicitly. We have employed the geometric configuration of points and lines in general position to deduce the formulation of 3D invariants. It has been verified in our experiments that our proposed method is considerably accurate when compared with the ground truth, and more efficient when compared with reconstruction based methods.

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Figueiredo, Pedro, Leandro Machado, João Vilas-Boas, and Ricardo Fernandes. "Reconstruction Error of Calibration Volume's Coordinates for 3D Swimming Kinematics." Journal of Human Kinetics 29, no. 1 (September 1, 2011): 35–40. http://dx.doi.org/10.2478/v10078-011-0037-6.

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Reconstruction Error of Calibration Volume's Coordinates for 3D Swimming KinematicsThe aim of this study was to investigate the accuracy and reliability of above and underwater 3D reconstruction of three calibration volumes with different control points disposal (#1 - on vertical and horizontal rods; #2 - on vertical and horizontal rods and facets; #3 - on crossed horizontal rods). Each calibration volume (3 × 2 × 3 m) was positioned in a 25 m swimming pool (half above and half below the water surface) and recorded with four underwater and two above water synchronised cameras (50 Hz). Reconstruction accuracy was determined calculating the RMS error of twelve validation points. The standard deviation across all digitisation of the same marker was used for assessing the reliability estimation. Comparison among different number of control points showed that the set of 24 points produced the most accurate results. The volume #2 presented higher accuracy (RMS errors: 5.86 and 3.59 mm for × axis, 3.45 and 3.11 mm for y axis and 4.38 and 4.00 mm for z axis, considering under and above water, respectively) and reliability (SD: underwater cameras ± [0.2; 0.6] mm; above water cameras ± [0.2; 0.3] mm) that may be considered suitable for 3D swimming kinematic analysis. Results revealed that RMS error was greater during underwater analysis, possibly due to refraction.

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Xiang, Hui Yu, Baoan Han, Jia Jun Huang, and Zhe Li. "Surface Reconstruction of Stamping Parts Based on Binocular Stereo Vision." Applied Mechanics and Materials 415 (September 2013): 314–17. http://dx.doi.org/10.4028/www.scientific.net/amm.415.314.

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In order to realize the 3D reconstruction of stamping parts surface, this paper based on binocular stereo vision principle firstly introduces the model of the binocular cameras. Internal and external parameters of camera can be obtained by binocular calibration, taking the printed circle grid centers which are on the stamping parts as feature points, and then using the disparity image obtained by HALCON to reconstruct 3D information of the feature points. Finally, use Matlab to plot out the scatter diagram of feature points and the fitting curved surface diagram.

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Cheng, Jun Ting, and Xin Kuan Liu. "Research on Surface Reconstruction from Intersecting Curves." Applied Mechanics and Materials 701-702 (December 2014): 145–49. http://dx.doi.org/10.4028/www.scientific.net/amm.701-702.145.

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This paper comes up with an stereo matching method for handy-scanner based on cross light. The handy-scan system with two cameras and one cross laser beam can scan very detail accurately through cross laser. 3D information is gained by dealing with cross laser image. What we do aims at estimating the transformation of the measured objects under the world coordinate. In order to achieve this goal, firstly we use 8-points algorithm to compute fundamental matrix. Then, the points on the left and the right can be matched based on fundamental matrix. The 3D coordinates of the point on the cross laser can be obtained by triangulation and curve surface differential. The experiment proves that this algorithm solves the problem of calculating the matching points in disorder. And in some way, it increases efficiency of matching cross laser stripes.

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Zhu, Meng Qiang, and Jie Yang. "Acquisition of Point Cloud Data in 3D Reconstruction." Applied Mechanics and Materials 536-537 (April 2014): 213–17. http://dx.doi.org/10.4028/www.scientific.net/amm.536-537.213.

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This paper takes the following measures to solve the problem of 3D reconstruction. Camera calibration is based on chessboard, taking several different attitude images. Use corner point coordinates by corner detection to process camera calibration. The calibration result is important to be used to correct the distorted image. Next, the left and right images should be matched to find out the object surface points’ imaging position respectively so that the object depth can be calculated by triangulation. According to the inverse process of projection mapping, we can project the object depth and disparity information into 3D space. As a result, we can obtain dense point cloud, which is ready for 3D reconstruction.

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Behrad, Alireza, and Nadia Roodsarabi. "3D Human Motion Tracking and Reconstruction Using DCT Matrix Descriptor." ISRN Machine Vision 2012 (May 7, 2012): 1–11. http://dx.doi.org/10.5402/2012/235396.

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One of the most important issues in human motion analysis is the tracking and 3D reconstruction of human motion, which utilizes the anatomic points' positions. These points can uniquely define the position and orientation of all anatomical segments. In this work, a new method is proposed for tracking and 3D reconstruction of human motion from the image sequence of a monocular static camera. In this method, 2D tracking is used for 3D reconstruction, which a database of selected frames is used for the correction of tracking process. The method utilizes a new image descriptor based on discrete cosine transform (DCT), which is employed in different stages of the algorithm. The advantage of using this descriptor is the capabilities of selecting proper frequency regions in various tasks, which results in an efficient tracking and pose matching algorithms. The tracking and matching algorithms are based on reference descriptor matrixes (RDMs), which are updated after each stage based on the frequency regions in DCT blocks. Finally, 3D reconstruction is performed using Taylor’s method. Experimental results show the promise of the algorithm.

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Sakaue, Fumihiko, Masaaki Takami, and Jun Sato. "Space Time Carving for Shape and Motion Recovery." International Journal of Virtual Reality 9, no. 1 (January 1, 2010): 7–12. http://dx.doi.org/10.20870/ijvr.2010.9.1.2755.

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Recently, a lot of methods for shape and motion reconstruction have been studied extensively. This paper describes a method for simultaneous shape and motion reconstruction without any corresponding points. We call the method space-time carving. The proposed method is based on a space carving method which can reconstruct 3D shape without any corresponding points. The method uses photo-consistency for 3D space carving. Our proposed method also uses photo-consistency for carving high dimensional space which represents not only shape but also motion. As a result, the proposed method can recover not only 3D shapes but also 3D motions of objects. The experimental results show that the proposed method works well.

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Wang, Hao, Guo Jun Tong, Tao Wang, and Li Wen Wang. "3D Model Reconstruction of the Broken Aero Engine Blade Based on the Detection Operator." Key Engineering Materials 693 (May 2016): 1289–93. http://dx.doi.org/10.4028/www.scientific.net/kem.693.1289.

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This paper made the digital model reconstruction of the RB211 high pressure turban blade. First, collected rough points cloud data by using visual measuring equipment. Then, finished pre-processing the point cloud data, took the rational simplification. Finally, a new algorithm was used to reconstructing the 3D digital model. The results proved that this method improved smoothness of the model, and reduced time and cost of modeling and machining.

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Yuan, Jian Ying, Xian Yong Liu, and Zhi Qiang Qiu. "A Robust Feature Points Matching Algorithm in 3D Optical Measuring System." Advanced Materials Research 383-390 (November 2011): 5193–99. http://dx.doi.org/10.4028/www.scientific.net/amr.383-390.5193.

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In optical measuring system with a handheld digital camera, image points matching is very important for 3-dimensional(3D) reconstruction. The traditional matching algorithms are usually based on epipolar geometry or multi-base lines. Mistaken matching points can not be eliminated by epipolar geometry and many matching points will be lost by multi-base lines. In this paper, a robust algorithm is presented to eliminate mistaken matching feature points in the process of 3D reconstruction from multiple images. The algorithm include three steps: (1) pre-matching the feature points using constraints of epipolar geometry and image topological structure firstly; (2) eliminating the mistaken matching points by the principle of triangulation in multi-images; (3) refining camera external parameters by bundle adjustment. After the external parameters of every image refined, repeat step (1) to step (3) until all the feature points been matched. Comparative experiments with real image data have shown that mistaken matching feature points can be effectively eliminated, and nearly no matching points have been lost, which have a better performance than traditonal matching algorithms do.

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Journal articles on the topic 'Points for 3D reconstruction'

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