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Journal articles on the topic 'Structured-light-stereo'

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Author: Grafiati

Published: 6 September 2023

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1

Pribanic, Tomislav, Nenad Obradovic, and Joaquim Salvi. "Stereo computation combining structured light and passive stereo matching." Optics Communications 285, no. 6 (March 2012): 1017–22. http://dx.doi.org/10.1016/j.optcom.2011.10.045.

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2

Du, Qiuchen, Rongke Liu, Boshen Guan, Yu Pan, and Shuqiao Sun. "Stereo-Matching Network for Structured Light." IEEE Signal Processing Letters 26, no. 1 (January 2019): 164–68. http://dx.doi.org/10.1109/lsp.2018.2883865.

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3

Jang, Wonkwi, Changsoo Je, Yongduek Seo, and Sang Wook Lee. "Structured-light stereo: Comparative analysis and integration of structured-light and active stereo for measuring dynamic shape." Optics and Lasers in Engineering 51, no. 11 (November 2013): 1255–64. http://dx.doi.org/10.1016/j.optlaseng.2013.05.001.

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4

Park, Min‐Gyu, Jonghee Park, Yongho Shin, Eul‐Gyoon Lim, and Kuk‐Jin Yoon. "Stereo vision with image‐guided structured‐light pattern matching." Electronics Letters 51, no. 3 (February 2015): 238–39. http://dx.doi.org/10.1049/el.2014.3770.

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5

Gao, Gui, Xi Chen Yang, and Hai Ming Zhang. "A Fast Structured Light Matching Method in Robot Stereo Vision." Applied Mechanics and Materials 29-32 (August 2010): 1981–84. http://dx.doi.org/10.4028/www.scientific.net/amm.29-32.1981.

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3D surface reconstruction has been widely used in reverse engineering, remanufacturing and automatic measurement. Binocular stereo imaging technology is the main method to obtain 3D information. Images are acquired from different positions of the object. The 3D coordinates of the point can be calculated according to the point’s coordinates in left and right cameras. The key to ensure the accuracy of 3D reconstruction is high precision and fast matching method of two images. As the image feature was not obvious, structured light is used. For its easy identification and extraction, the method has been more and more widely used. But the former research cannot ensure the matching exactness or matching algorithm takes too much time. In order to improve the precision and efficiency of 3D measurement, a fast and simple structured light matching method is designed based on epipolar geometry. This method can ensure 100% matching accuracy. It does not need other assistant tool except for structured light projector. On the beginning of the measurement, structured light is projected onto the object to be measured. Two images of the object with structured light are captured by two cameras in different positions. Structured lights extracted from the two images are matched by the new algorithm. The 3D coordinate of this structured light is calculated. The position of structured light is changed on the object till completed. From a lot of experiments, the proposed grating matching method is proved and it is a technique with high precision, low costs, easy operation, and an automatically matching method. Furthermore, it can be widely used in most of 3D reconstruction system.

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Barone, S., P. Neri, A. Paoli, and A. V. Razionale. "Structured light stereo catadioptric scanner based on a spherical mirror." Optics and Lasers in Engineering 107 (August 2018): 1–12. http://dx.doi.org/10.1016/j.optlaseng.2018.03.004.

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7

Du, Jun, Ling Yu Yong, Mei Sun, and Jia Sheng Ge. "Study on Stereo Vision for 3D Reconstruction of Welding Seam." Advanced Materials Research 850-851 (December 2013): 212–16. http://dx.doi.org/10.4028/www.scientific.net/amr.850-851.212.

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The Monocular stereo vision sensor based on structured light is designed and invented for the detection of the weld seam. By incorporating the structured light, the corresponding points matching problem in the stereo vision has been solved effectively. Firstly, the built monocular stereo vision system is used to obtain the image information of seam surface. Then the image coordinate of the seam feature points in the two-dimensional plane can be identified and extracted, through the responding image processing and feature analysis of the seam image collected. After that, the three-dimensional coordinates are calculated by using the theory of projective geometry according to the positional relation between the CCD camera and structured light projected in the seam surface. By this way, the seam feature information such as the three-dimensional geometry sizes, the groove type, the angle, and the interval can be obtained. Finally, the algorithm performance is tested by the experiment of obtaining the three-dimensional coordinate for seams center points, and the results have proved the detection accuracy and reliability of the visual collection system.

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8

Liu, Yu Bao, Bin Liu, and Jun Yi Lin. "A Method of Line Structured Light Vision System Calibration Based on Stereo Vision." Applied Mechanics and Materials 397-400 (September 2013): 1453–58. http://dx.doi.org/10.4028/www.scientific.net/amm.397-400.1453.

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It is a difficult task to get enough numbers of highly accurate control points for projector calibration in line structured light vision system. A new projector calibration method based on binocular stereo vision is proposed in this paper. Two cameras calibration can be done usingtraditional camera calibration method and they composed a binocular stereo vision. In projector calibration procedure, a planar template was located at several different positions in front of the stereo vision system. Two cameras captured the stripe images in each position simultaneously. Every center points of the laser stripe can be used as control points of the projector plane. The 3D coordinate of the stripe center points can be obtained through binocular stereo vision principle easily. So the light plane can be calculated quickly. Experiments were carried out and the result shows that the proposed method is flexible and stable.

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9

Li, Meiying, Jin Liu, Haima Yang, Wanqing Song, and Zihao Yu. "Structured Light 3D Reconstruction System Based on a Stereo Calibration Plate." Symmetry 12, no. 5 (May 7, 2020): 772. http://dx.doi.org/10.3390/sym12050772.

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Calibration is a critical step in structured light 3D imaging systems. However, in the traditional calibration process, since the calibration plate is based on a two-dimensional model, the flatness of the calibration plate and the angle of the photo will affect the subsequent stitching steps based on the feature points. The number of photos also affects the calibration results. To improve the calibration accuracy, multiple photos need to be taken. The primary objective of this study was to achieve the simple and fast calibration of system parameters, so a method obtaining a large number of calibration data by homography matrix is presented, and a corresponding stereo target is designed in symmetry. First, using the relationship between the corner coordinates of the left and right parts of the stereo calibration plate and the coordinates of the world coordinate system, the homography matrix of the left and right calibration plates from the image coordinates to the world coordinates is calculated. Second, all the pixels in the stereo calibration plate are matched to the world coordinate system by using the homography matrix. In addition, we also compared the results of this method with those of traditional calibration methods. The experimental results show that the 3D geometric surface of the reconstruction result is smooth, it avoids the missing parts and the visual effect is excellent. Furthermore, the error range of small and complex objects can be reduced to 0.03 mm~0.05 mm. This method simplifies the calibration steps, reduces the calibration costs and has practical application value.

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10

Peng, Kai, Xing Lin Zhou, and Ji Guang Liu. "Obstacle Detection System Based on Stereo Vision and a Structured Light." Advanced Materials Research 424-425 (January 2012): 1070–74. http://dx.doi.org/10.4028/www.scientific.net/amr.424-425.1070.

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Obstacle detection is a crucial issue for pilotless device guidance function and it has to be performed with high reliability to avoid any potential collision with the front object. The vision-based obstacle detection systems are regarded perfect for this purpose because they require little on all kind of condition. In this paper, an obstacle detection system using stereo vision sensors and structured light is developed. This system realizes rapid feature matching and high precision measurement distance with the help of structured light, avoiding the time-consuming of the initial corresponding pairs. After the initial detection, the system executes the tracking light strip algorithm for the obstacles. The proposed system can detect a front obstacle in vision field and obtain the size of obstacle. The proposed obstacle detection system is set up and its performance is verified experimentally

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11

Bruno, F., G. Bianco, M. Muzzupappa, S. Barone, and A. V. Razionale. "Experimentation of structured light and stereo vision for underwater 3D reconstruction." ISPRS Journal of Photogrammetry and Remote Sensing 66, no. 4 (July 2011): 508–18. http://dx.doi.org/10.1016/j.isprsjprs.2011.02.009.

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12

Garcia, Ricardo R., and Avideh Zakhor. "Consistent Stereo-Assisted Absolute Phase Unwrapping Methods for Structured Light Systems." IEEE Journal of Selected Topics in Signal Processing 6, no. 5 (September 2012): 411–24. http://dx.doi.org/10.1109/jstsp.2012.2195157.

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13

Kaczmarek, Adam L. "3D Vision System for a Robotic Arm Based on Equal Baseline Camera Array." Journal of Intelligent & Robotic Systems 99, no. 1 (December 4, 2019): 13–28. http://dx.doi.org/10.1007/s10846-019-01117-8.

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AbstractThis paper presents a lightweight 3D vision system called Equal Baseline Camera Array (EBCA). EBCA can work in different light conditions and it can be applied for measuring large range of distances. The system is a useful alternative to other known distance measuring devices such as structured-light 3D scanners, time-of-flight cameras, Light Detection and Ranging (LIDAR) devices and structure from motion techniques. EBCA can be mounted on a robotic arm without putting significant load on its construction. EBCA consists of a central camera and a ring of side cameras. The system uses stereo matching algorithms to acquire disparity maps and depth maps similarly as in case of using stereo cameras. This paper introduces methods of adapting stereo matching algorithms designed for stereo cameras to EBCA. The paper also presents the analysis of local, semi-global and global stereo matching algorithms in the context of the EBCA usage. Experiments show that, on average, results obtained from EBCA contain 37.49% less errors than the results acquired from a single stereo camera used in the same conditions.

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14

Raju, Viprav B., and Edward Sazonov. "FOODCAM: A Novel Structured Light-Stereo Imaging System for Food Portion Size Estimation." Sensors 22, no. 9 (April 26, 2022): 3300. http://dx.doi.org/10.3390/s22093300.

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Imaging-based methods of food portion size estimation (FPSE) promise higher accuracies compared to traditional methods. Many FPSE methods require dimensional cues (fiducial markers, finger-references, object-references) in the scene of interest and/or manual human input (wireframes, virtual models). This paper proposes a novel passive, standalone, multispectral, motion-activated, structured light-supplemented, stereo camera for food intake monitoring (FOODCAM) and an associated methodology for FPSE that does not need a dimensional reference given a fixed setup. The proposed device integrated a switchable band (visible/infrared) stereo camera with a structured light emitter. The volume estimation methodology focused on the 3-D reconstruction of food items based on the stereo image pairs captured by the device. The FOODCAM device and the methodology were validated using five food models with complex shapes (banana, brownie, chickpeas, French fries, and popcorn). Results showed that the FOODCAM was able to estimate food portion sizes with an average accuracy of 94.4%, which suggests that the FOODCAM can potentially be used as an instrument in diet and eating behavior studies.

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Raju, Viprav B., and Edward Sazonov. "FOODCAM: A Novel Structured Light-Stereo Imaging System for Food Portion Size Estimation." Sensors 22, no. 9 (April 26, 2022): 3300. http://dx.doi.org/10.3390/s22093300.

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Imaging-based methods of food portion size estimation (FPSE) promise higher accuracies compared to traditional methods. Many FPSE methods require dimensional cues (fiducial markers, finger-references, object-references) in the scene of interest and/or manual human input (wireframes, virtual models). This paper proposes a novel passive, standalone, multispectral, motion-activated, structured light-supplemented, stereo camera for food intake monitoring (FOODCAM) and an associated methodology for FPSE that does not need a dimensional reference given a fixed setup. The proposed device integrated a switchable band (visible/infrared) stereo camera with a structured light emitter. The volume estimation methodology focused on the 3-D reconstruction of food items based on the stereo image pairs captured by the device. The FOODCAM device and the methodology were validated using five food models with complex shapes (banana, brownie, chickpeas, French fries, and popcorn). Results showed that the FOODCAM was able to estimate food portion sizes with an average accuracy of 94.4%, which suggests that the FOODCAM can potentially be used as an instrument in diet and eating behavior studies.

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16

Wang, B., W. Liu, Z. Jia, X. Lu, and Y. Sun. "Dimensional measurement of hot, large forgings with stereo vision structured light system." Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 225, no. 6 (June 2011): 901–8. http://dx.doi.org/10.1177/2041297510393513.

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17

Liu, Kun, Changhe Zhou, Shengbin Wei, Shaoqing Wang, Xin Fan, and Jianyong Ma. "Optimized stereo matching in binocular three-dimensional measurement system using structured light." Applied Optics 53, no. 26 (September 10, 2014): 6083. http://dx.doi.org/10.1364/ao.53.006083.

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18

Li, Zhong Yang, Ze Yuan Liu, Bai Tong Wang, and Xiu Xiang Huang. "3D Body Measurement System Based on Structured Light." Advanced Materials Research 503-504 (April 2012): 1280–83. http://dx.doi.org/10.4028/www.scientific.net/amr.503-504.1280.

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This paper presents a 3D body measurement system based on structured light. We analyze the principal of projection profile measurement and model binocular system with two cameras which comprise a stereo vision system. The goal of calibration method is to achieve the high accuracy for human body dimensions. The system software based on VS 2008 and OpenGL provides a visual interface with standard data interface for CAD/CAM.

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19

Song, Zhao, Zhan Song, and Yuping Ye. "Eliminating the Effect of Reflectance Properties on Reconstruction in Stripe Structured Light System." Sensors 20, no. 22 (November 17, 2020): 6564. http://dx.doi.org/10.3390/s20226564.

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The acquisition of the geometry of general scenes is related to the interplay of surface geometry, material properties and illumination characteristics. Surface texture and non-Lambertian reflectance properties degrade the reconstruction results by structured light technique. Existing structured light techniques focus on different coding strategy and light sources to improve reconstruction accuracy. The hybrid system consisting of a structured light technique and photometric stereo combines the depth value with normal information to refine the reconstruction results. In this paper, we propose a novel hybrid system consisting of stripe-based structured light and photometric stereo. The effect of surface texture and non-Lambertian reflection on stripe detection is first concluded. Contrary to existing fusion strategy, we propose an improved method for stripe detection to reduce the above factor’s effects on accuracy. The reconstruction problem for general scene comes down to using reflectance properties to improve the accuracy of stripe detection. Several objects, including checkerboard, metal-flat plane and free-form objects with complex reflectance properties, were reconstructed to validate our proposed method, which illustrates the effectiveness on improving the reconstruction accuracy of complex objects. The three-step phase-shifting algorithm was implemented and the reconstruction results were given and also compared with ours. In addition, our proposed framework provides a new feasible scheme for solving the ongoing problem of the reconstruction of complex objects with variant reflectance. The problem can be solved by subtracting the non-Lambertian components from the original grey values of stripe to improve the accuracy of stripe detection. In the future, based on stripe structured light technique, more general reflection models can be used to model different types of reflection properties of complex objects.

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20

Kniaz, V. V., V. A. Mizginov, L. V. Grodzitkiy, N. A. Fomin, and V. A. Knyaz. "DENSE 3D OBJECT RECONSTRUCTION USING STRUCTURED-LIGHT SCANNER AND DEEP LEARNING." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B2-2020 (August 12, 2020): 777–83. http://dx.doi.org/10.5194/isprs-archives-xliii-b2-2020-777-2020.

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Abstract. Structured light scanners are intensively exploited in various applications such as non-destructive quality control at an assembly line, optical metrology, and cultural heritage documentation. While more than 20 companies develop commercially available structured light scanners, structured light technology accuracy has limitations for fast systems. Model surface discrepancies often present if the texture of the object has severe changes in brightness or reflective properties of its texture. The primary source of such discrepancies is errors in the stereo matching caused by complex surface texture. These errors result in ridge-like structures on the surface of the reconstructed 3D model. This paper is focused on the development of a deep neural network LineMatchGAN for error reduction in 3D models produced by a structured light scanner. We use the pix2pix model as a starting point for our research. The aim of our LineMatchGAN is a refinement of the rough optical flow A and generation of an error-free optical flow B̂. We collected a dataset (which we term ZebraScan) consisting of 500 samples to train our LineMatchGAN model. Each sample includes image sequences (Sl, Sr), ground-truth optical flow B and a ground-truth 3D model. We evaluate our LineMatchGAN on a test split of our ZebraScan dataset that includes 50 samples. The evaluation proves that our LineMatchGAN improves the stereo matching accuracy (optical flow end point error, EPE) from 0.05 pixels to 0.01 pixels.

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Liu, Bin, Fan Yang, Yixuan Huang, Ye Zhang, and Guanhao Wu. "Single-Shot Three-Dimensional Reconstruction Using Grid Pattern-Based Structured-Light Vision Method." Applied Sciences 12, no. 20 (October 20, 2022): 10602. http://dx.doi.org/10.3390/app122010602.

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Structured-light vision methods are widely employed for three-dimensional reconstruction. As a typical structured light pattern, grid pattern is extensively applied in single-shot three-dimensional reconstruction. The uniqueness of the grid feature retrieval is critical to the reconstruction. Most methods using grid pattern utilize the epipolar constraint to retrieve the correspondence. However, the low calibration accuracy of the camera–projector stereo system may impact the correspondence retrieval. An approach using grid pattern-based structured-light vision method is proposed. The grid pattern-based structured-light model was combined with the camera model and the multiple light plane equations. An effective extraction method of the grid stripe features was investigated. The system calibration strategy, based on coplanar constraint, is presented. The experimental setup consisted of a camera and an LED projector. Experiments were carried out to verify the accuracy of the proposed method.

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22

Zhang, Chi, Zhong Wei Li, and Yu Sheng Shi. "Key Technology in Thermal State Measurement Based on Structured Light Stereo Vision Technique." Applied Mechanics and Materials 268-270 (December 2012): 1632–36. http://dx.doi.org/10.4028/www.scientific.net/amm.268-270.1632.

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In order to realize online measurement of object in thermal state, a method based on blue structured light stereo vision technique was presented. The key technology includes high brightness blue projection solutions, physical and digital filtering method reducing red thermal radiation, phase shifting and multi-frequency heterodyne principle. The point cloud data could be calculated by projecting 12 or 24 raster images. The experiment proves that the method has advantage of high-speed and high- precision, and it is also simple and convenient, this can meet the requirements of online measurement of medium and small forgings in thermal state.

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23

Barone, Sandro, Alessandro Paoli, and Armando Viviano Razionale. "Three-dimensional point cloud alignment detecting fiducial markers by structured light stereo imaging." Machine Vision and Applications 23, no. 2 (May 15, 2011): 217–29. http://dx.doi.org/10.1007/s00138-011-0340-1.

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24

Li, Fu, Quanlu Li, Tianjiao Zhang, Yi Niu, and Guangming Shi. "Depth acquisition with the combination of structured light and deep learning stereo matching." Signal Processing: Image Communication 75 (July 2019): 111–17. http://dx.doi.org/10.1016/j.image.2019.04.001.

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25

Li, Baizhen, Zhijie Xu, Feng Gao, Yanlong Cao, and Quancheng Dong. "3D Reconstruction of High Reflective Welding Surface Based on Binocular Structured Light Stereo Vision." Machines 10, no. 2 (February 20, 2022): 159. http://dx.doi.org/10.3390/machines10020159.

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The inspection of welding surface quality is an important task for welding work. With the development of product quality inspection technology, automated and machine vision-based inspection have been applied to more industrial application fields because of its non-contact, convenience, and high efficiency. However, challenging material and optical phenomena such as high reflective surface areas often present on welding seams tend to produce artifacts such as holes in the reconstructed model using current visual sensors, hence leading to insufficiency or even errors in the inspection result. This paper presents a 3D reconstruction technique for highly reflective welding surfaces based on binocular style structured light stereo vision. The method starts from capturing a fully lit image for identifying highly reflective regions on a welding surface using conventional computer vision models, including gray-scale, binarization, dilation, and erosion. Then, fringe projection profilometry is used to generate point clouds on the interested area. The mapping and alignment from 2D image to 3D point cloud is then established to highlight features that are vital for eliminating “holes”—large featureless areas—caused by high reflections such as the specular mirroring effect. A two-way slicing method is proposed to operate on the refined point cloud, following the concept of dimensionality reduction to project the sliced point cloud onto different image planes before a Smoothing Spline model is applied to fit the discrete point formed by projection. The 3D coordinate values of points in the “hole” region are estimated according to the fitted curves and appended to the original point cloud using iterative algorithms. Experiment results verify that the proposed method can accurately reconstruct a wide range of welding surfaces with significantly improved precision.

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26

Kim, Min Young, Shirazi Muhammad Ayaz, Jaechan Park, and YoungJun Roh. "Adaptive 3D sensing system based on variable magnification using stereo vision and structured light." Optics and Lasers in Engineering 55 (April 2014): 113–27. http://dx.doi.org/10.1016/j.optlaseng.2013.10.021.

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27

Gu, Feifei, Zhan Song, and Zilong Zhao. "Single-Shot Structured Light Sensor for 3D Dense and Dynamic Reconstruction." Sensors 20, no. 4 (February 17, 2020): 1094. http://dx.doi.org/10.3390/s20041094.

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Structured light (SL) has a trade-off between acquisition time and spatial resolution. Temporally coded SL can produce a 3D reconstruction with high density, yet it is not applicable to dynamic reconstruction. On the contrary, spatially coded SL works with a single shot, but it can only achieve sparse reconstruction. This paper aims to achieve accurate 3D dense and dynamic reconstruction at the same time. A speckle-based SL sensor is presented, which consists of two cameras and a diffractive optical element (DOE) projector. The two cameras record images synchronously. First, a speckle pattern was elaborately designed and projected. Second, a high-accuracy calibration method was proposed to calibrate the system; meanwhile, the stereo images were accurately aligned by developing an optimized epipolar rectification algorithm. Then, an improved semi-global matching (SGM) algorithm was proposed to improve the correctness of the stereo matching, through which a high-quality depth map was achieved. Finally, dense point clouds could be recovered from the depth map. The DOE projector was designed with a size of 8 mm × 8 mm. The baseline between stereo cameras was controlled to be below 50 mm. Experimental results validated the effectiveness of the proposed algorithm. Compared with some other single-shot 3D systems, our system displayed a better performance. At close range, such as 0.4 m, our system could achieve submillimeter accuracy.

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Lin, Jun Yi, Kai Yong Jiang, Chang Biao Huang, and Bin Liu. "Global Calibration Method for a Multi-Sensor Measurement System Based on Structured Light Stereo Vision." Advanced Materials Research 542-543 (June 2012): 684–89. http://dx.doi.org/10.4028/www.scientific.net/amr.542-543.684.

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The global calibration of multi-sensor measurement system is difficult to accomplish, usually, it needs external high-precision measurement equipment. A novel global calibration method based on common planar template is proposed. Stereo vision combined with laser linear-structured light is adopted to constitute a 3D vision sensor system (3DVSS). Stereo calibration of the 3DVSS can be finished by the planar template calibration method. For the global calibration of multiple vision sensors, it only needs a common planar template which is one of the planar templates can be seen synchronously by every camera in 3DVSS. The homography matrix between the coordinate systems of the 3DVSS and the common planer template can be calculated. The global coordinate is established in the common planar template, so the local coordinate system (LCS) of each 3DVSS can be transformed to the global coordinate system (GCS) through the common planar template. Two experiments have been used to test the proposed method, and the experimental results show that the proposed method is flexible and effective.

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Kaczmarek, Adam L., and Bernhard Blaschitz. "Equal Baseline Camera Array—Calibration, Testbed and Applications." Applied Sciences 11, no. 18 (September 12, 2021): 8464. http://dx.doi.org/10.3390/app11188464.

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This paper presents research on 3D scanning by taking advantage of a camera array consisting of up to five adjacent cameras. Such an array makes it possible to make a disparity map with a higher precision than a stereo camera, however it preserves the advantages of a stereo camera such as a possibility to operate in wide range of distances and in highly illuminated areas. In an outdoor environment, the array is a competitive alternative to other 3D imaging equipment such as Structured-light 3D scanners or Light Detection and Ranging (LIDAR). The considered kinds of arrays are called Equal Baseline Camera Array (EBCA). This paper presents a novel approach to calibrating the array based on the use of self-calibration methods. This paper also introduces a testbed which makes it possible to develop new algorithms for obtaining 3D data from images taken by the array. The testbed was released under open-source. Moreover, this paper shows new results of using these arrays with different stereo matching algorithms including an algorithm based on a convolutional neural network and deep learning technology.

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Mei, Junhui, Xiao Yang, Zhenxin Wang, Xiaobo Chen, and Juntong Xi. "A Topology-Based Stereo Matching Method for One Shot 3D Measurement Using Coded Spot-Array Structured Light." Sensors 21, no. 19 (September 27, 2021): 6444. http://dx.doi.org/10.3390/s21196444.

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In this paper, a topology-based stereo matching method for 3D measurement using a single pattern of coded spot-array structured light is proposed. The pattern of spot array is designed with a central reference ring spot, and each spot in the pattern can be uniquely coded with the row and column indexes according to the predefined topological search path. A method using rectangle templates to find the encoded spots in the captured images is proposed in the case where coding spots are missing, and an interpolation method is also proposed for rebuilding the missing spots. Experimental results demonstrate that the proposed technique could exactly and uniquely decode each spot and establish the stereo matching relation successfully, which can be used to obtain three-dimensional (3D) reconstruction with a single-shot method.

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31

Lilienblum, Erik, and Ayoub Al-Hamadi. "A Structured Light Approach for 3-D Surface Reconstruction With a Stereo Line-Scan System." IEEE Transactions on Instrumentation and Measurement 64, no. 5 (May 2015): 1258–66. http://dx.doi.org/10.1109/tim.2014.2364105.

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32

Barone, S., P. Neri, A. Paoli, and A. V. Razionale. "3D acquisition and stereo-camera calibration by active devices: A unique structured light encoding framework." Optics and Lasers in Engineering 127 (April 2020): 105989. http://dx.doi.org/10.1016/j.optlaseng.2019.105989.

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33

Ye, Yuping, Siyuan Hao, Zhan Song, Feifei Gu, and Juan Zhao. "A novel triangular stereo model for 3D reconstruction of uniaxial MEMS-based structured light system." Optics and Lasers in Engineering 166 (July 2023): 107596. http://dx.doi.org/10.1016/j.optlaseng.2023.107596.

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34

Kong, Lingyin, Wei Xiong, and Sancong Ying. "Spatiotemporal Matching Cost Function Based on Differential Evolutionary Algorithm for Random Speckle 3D Reconstruction." Applied Sciences 12, no. 9 (April 20, 2022): 4132. http://dx.doi.org/10.3390/app12094132.

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Random speckle structured light can increase the texture information of the object surface, so it is added in the binocular stereo vision system to solve the matching ambiguity problem caused by the surface with repetitive pattern or no texture. To improve the reconstruction quality, many current researches utilize multiple speckle patterns for projection and use stereo matching methods based on spatiotemporal correlation. This paper presents a novel random speckle 3D reconstruction scheme, in which multiple speckle patterns are used and a weighted-fusion-based spatiotemporal matching cost function (STMCF) is proposed to find the corresponding points in speckle stereo image pairs. Furthermore, a parameter optimization method based on differential evolutionary (DE) algorithm is designed for automatically determining the values of all parameters included in STMCF. In this method, since there is no suitable training data with ground truth, we explore a training strategy where a passive stereo vision dataset with ground truth is used as training data and then apply the learned parameter value to the stereo matching of speckle stereo image pairs. Various experimental results verify that our scheme can realize accurate and high-quality 3D reconstruction efficiently and the proposed STMCF exhibits superior performance in terms of accuracy, computation time and reconstruction quality than the state-of-the-art method based on spatiotemporal correlation.

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Belter, Dominik, Przemysław Łabecki, Péter Fankhauser, and Roland Siegwart. "RGB–D terrain perception and dense mapping for legged robots." International Journal of Applied Mathematics and Computer Science 26, no. 1 (March 1, 2016): 81–97. http://dx.doi.org/10.1515/amcs-2016-0006.

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Abstract This paper addresses the issues of unstructured terrain modeling for the purpose of navigation with legged robots. We present an improved elevation grid concept adopted to the specific requirements of a small legged robot with limited perceptual capabilities. We propose an extension of the elevation grid update mechanism by incorporating a formal treatment of the spatial uncertainty. Moreover, this paper presents uncertainty models for a structured light RGB-D sensor and a stereo vision camera used to produce a dense depth map. The model for the uncertainty of the stereo vision camera is based on uncertainty propagation from calibration, through undistortion and rectification algorithms, allowing calculation of the uncertainty of measured 3D point coordinates. The proposed uncertainty models were used for the construction of a terrain elevation map using the Videre Design STOC stereo vision camera and Kinect-like range sensors. We provide experimental verification of the proposed mapping method, and a comparison with another recently published terrain mapping method for walking robots.

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Chen Yilin, 陈亦麟, 王发宇 Wang Fayu, and 刘建阳 Liu Jianyang. "基于双目立体视觉与结构光的便携式非接触三维掌纹采集系统." Laser & Optoelectronics Progress 59, no. 4 (2022): 0410016. http://dx.doi.org/10.3788/lop202259.0410016.

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Song, Zhao, Zhan Song, Juan Zhao, and Feifei Gu. "Micrometer-level 3D measurement techniques in complex scenes based on stripe-structured light and photometric stereo." Optics Express 28, no. 22 (October 19, 2020): 32978. http://dx.doi.org/10.1364/oe.401850.

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Wen, Xin, Kechen Song, Menghui Niu, Zhipeng Dong, and Yunhui Yan. "3D inspection technology combining passive stereo matching and active structured light for steel plate surface sample." International Journal of Surface Science and Engineering 11, no. 4 (2017): 299. http://dx.doi.org/10.1504/ijsurfse.2017.087422.

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Yan, Yunhui, Zhipeng Dong, Kechen Song, Menghui Niu, and Xin Wen. "3D inspection technology combining passive stereo matching and active structured light for steel plate surface sample." International Journal of Surface Science and Engineering 11, no. 4 (2017): 299. http://dx.doi.org/10.1504/ijsurfse.2017.10008361.

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Wang, Qingyu, Dihua Wu, Wei Liu, Mingzhao Lou, Huanyu Jiang, Yibin Ying, and Mingchuan Zhou. "PlantStereo: A High Quality Stereo Matching Dataset for Plant Reconstruction." Agriculture 13, no. 2 (January 29, 2023): 330. http://dx.doi.org/10.3390/agriculture13020330.

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Stereo matching is a depth perception method for plant phenotyping with high throughput. In recent years, the accuracy and real-time performance of the stereo matching models have been greatly improved. While the training process relies on specialized large-scale datasets, in this research, we aim to address the issue in building stereo matching datasets. A semi-automatic method was proposed to acquire the ground truth, including camera calibration, image registration, and disparity image generation. On the basis of this method, spinach, tomato, pepper, and pumpkin were considered for experiment, and a dataset named PlantStereo was built for reconstruction. Taking data size, disparity accuracy, disparity density, and data type into consideration, PlantStereo outperforms other representative stereo matching datasets. Experimental results showed that, compared with the disparity accuracy at pixel level, the disparity accuracy at sub-pixel level can remarkably improve the matching accuracy. More specifically, for PSMNet, the EPE and bad-3 error decreased 0.30 pixels and 2.13%, respectively. For GwcNet, the EPE and bad-3 error decreased 0.08 pixels and 0.42%, respectively. In addition, the proposed workflow based on stereo matching can achieve competitive results compared with other depth perception methods, such as Time-of-Flight (ToF) and structured light, when considering depth error (2.5 mm at 0.7 m), real-time performance (50 fps at 1046 × 606), and cost. The proposed method can be adopted to build stereo matching datasets, and the workflow can be used for depth perception in plant phenotyping.

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Veitch-Michaelis, Joshua, Jan-Peter Muller, David Walton, Jonathan Storey, Michael Foster, and Benjamin Crutchley. "ENHANCEMENT OF STEREO IMAGERY BY ARTIFICIAL TEXTURE PROJECTION GENERATED USING A LIDAR." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B5 (June 15, 2016): 599–606. http://dx.doi.org/10.5194/isprs-archives-xli-b5-599-2016.

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Passive stereo imaging is capable of producing dense 3D data, but image matching algorithms generally perform poorly on images with large regions of homogenous texture due to ambiguous match costs. Stereo systems can be augmented with an additional light source that can project some form of unique texture onto surfaces in the scene. Methods include structured light, laser projection through diffractive optical elements, data projectors and laser speckle. Pattern projection using lasers has the advantage of producing images with a high signal to noise ratio. We have investigated the use of a scanning visible-beam LIDAR to simultaneously provide enhanced texture within the scene and to provide additional opportunities for data fusion in unmatched regions. The use of a LIDAR rather than a laser alone allows us to generate highly accurate ground truth data sets by scanning the scene at high resolution. This is necessary for evaluating different pattern projection schemes. Results from LIDAR generated random dots are presented and compared to other texture projection techniques. Finally, we investigate the use of image texture analysis to intelligently project texture where it is required while exploiting the texture available in the ambient light image.

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42

Veitch-Michaelis, Joshua, Jan-Peter Muller, David Walton, Jonathan Storey, Michael Foster, and Benjamin Crutchley. "ENHANCEMENT OF STEREO IMAGERY BY ARTIFICIAL TEXTURE PROJECTION GENERATED USING A LIDAR." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B5 (June 15, 2016): 599–606. http://dx.doi.org/10.5194/isprsarchives-xli-b5-599-2016.

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Passive stereo imaging is capable of producing dense 3D data, but image matching algorithms generally perform poorly on images with large regions of homogenous texture due to ambiguous match costs. Stereo systems can be augmented with an additional light source that can project some form of unique texture onto surfaces in the scene. Methods include structured light, laser projection through diffractive optical elements, data projectors and laser speckle. Pattern projection using lasers has the advantage of producing images with a high signal to noise ratio. We have investigated the use of a scanning visible-beam LIDAR to simultaneously provide enhanced texture within the scene and to provide additional opportunities for data fusion in unmatched regions. The use of a LIDAR rather than a laser alone allows us to generate highly accurate ground truth data sets by scanning the scene at high resolution. This is necessary for evaluating different pattern projection schemes. Results from LIDAR generated random dots are presented and compared to other texture projection techniques. Finally, we investigate the use of image texture analysis to intelligently project texture where it is required while exploiting the texture available in the ambient light image.

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Lou, Xiao Ping, Nai Guang Lv, Peng Sun, and Yi Min Lin. "Data Registration Method Based on Three Dimensional Target." Applied Mechanics and Materials 103 (September 2011): 87–91. http://dx.doi.org/10.4028/www.scientific.net/amm.103.87.

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Data registration method using special three dimensional target to track the structured light measurement system is discussed. Optical scanning device, tracking target and stereo vision system are integrated together to fulfill profile inspection of large-scale free-form surface objects without extra mark points. System architecture and processing steps are introduced and layout optimization methods of three dimensional target are illustrated. Experimental results are showed to evaluate the validity of the registration method and suggests are given to improve the accuracy of the system.

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Ayaz, Shirazi Muhammad, Khan Danish, Joon-Young Bang, Soo-In Park, YoungJun Roh, and Min Young Kim. "A multi-view stereo based 3D hand-held scanning system using visual-inertial navigation and structured light." MATEC Web of Conferences 32 (2015): 06004. http://dx.doi.org/10.1051/matecconf/20153206004.

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Yin, Wei, Shijie Feng, Tianyang Tao, Lei Huang, Maciej Trusiak, Qian Chen, and Chao Zuo. "High-speed 3D shape measurement using the optimized composite fringe patterns and stereo-assisted structured light system." Optics Express 27, no. 3 (January 25, 2019): 2411. http://dx.doi.org/10.1364/oe.27.002411.

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Yang, Lei, En Li, Teng Long, Junfeng Fan, and Zize Liang. "A Novel 3-D Path Extraction Method for Arc Welding Robot Based on Stereo Structured Light Sensor." IEEE Sensors Journal 19, no. 2 (January 15, 2019): 763–73. http://dx.doi.org/10.1109/jsen.2018.2877976.

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Sun, Qingbo. "Research on RGB-D image recognition technology based on feature fusion and machine learning." Journal of Physics: Conference Series 2031, no. 1 (September 1, 2021): 012022. http://dx.doi.org/10.1088/1742-6596/2031/1/012022.

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Abstract The three-dimensional RGB-D image contains not only the color and texture information of the two-dimensional image, but also contains the surface geometry information of the target. This article analyzes the RGB-D image recognition methods, including stereo vision technology, structured light technology, etc. By studying the application points of RGB-D image recognition technology under the background of feature fusion and machine learning, the purpose is to improve the richness of image recognition content and provide reference for the smooth development of the follow-up work.

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Ham, Hanry, Julian Wesley, and Hendra Hendra. "Computer Vision Based 3D Reconstruction : A Review." International Journal of Electrical and Computer Engineering (IJECE) 9, no. 4 (August 1, 2019): 2394. http://dx.doi.org/10.11591/ijece.v9i4.pp2394-2402.

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3D reconstruction are used in many fields starts from the object reconstruction such as site, and cultural artifacts in both ground and under the sea levels. The scientist are beneficial for these task in order to learn and keep the environment into 3D data due to the extinction. In this paper explained vision setup that is commonly used such as single camera, stereo camera, Kinect / Structured Light/ Time of Flight camera and fusion approach. The prior works also explained how the 3D reconstruction perform in many fields and using various algorithms.

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Bräuer-Burchardt, Christian, Christoph Munkelt, Ingo Gebhart, Matthias Heinze, Stefan Heist, Peter Kühmstedt, and Gunther Notni. "A-Priori Calibration of a Structured Light Underwater 3D Sensor." Journal of Marine Science and Engineering 8, no. 9 (August 20, 2020): 635. http://dx.doi.org/10.3390/jmse8090635.

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In this study, we introduce a new calibration method for underwater optical stereo scanners. It uses air calibration, additional underwater parameters, and extended camera modeling. The new methodology can be applied to both passive photogrammetric and structured light three-dimensional (3D) scanning systems. The novel camera model uses a variable principal distance depending on the radial distance to the principal point instead of two-dimensional distortion functions. This allows for an initial improvement of 3D reconstruction quality. In a second step, certain underwater-specific parameters—such as refraction indices, glass thickness, and view-port distances—are determined. Finally, a correction function for the entire measurement volume can be obtained from a few underwater measurements. Its application further improves the measurement accuracy. Measurement examples show the performance of the new calibration method in comparison to current underwater calibration strategies. A discussion of the possibilities and limits of the new calibration method and an outlook for future work complete this work.

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Chiang, Pei-Ju, and Chang-Hao Lin. "Active Stereo Vision System with Rotated Structured Light Patterns and Two-Step Denoising Process for Improved Spatial Resolution." Optics and Lasers in Engineering 152 (May 2022): 106958. http://dx.doi.org/10.1016/j.optlaseng.2022.106958.

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