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Journal articles on the topic 'Computer stereo vision'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

Zhang, Ke, and Han Pin Luo. "A Fast Linear Calibration of Computer Stereo Vision System." Advanced Materials Research 305 (July 2011): 372–77. http://dx.doi.org/10.4028/www.scientific.net/amr.305.372.

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Computer stereo vision has been paid high attention in areas such as industry measurement and automatic control. Calibration of stereo vision system is a key step to implement vision measurement. Nonlinear calibration method involves too many parameters and too complex function, so the processing of optimization is difficult and slow. In this paper, two digital cameras are used to set up stereo vision system which provides convenient experimental operation. The binocular stereo vision system is calibrated using linear calibration model. The results indicate that the method is stable and fast w

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Díaz, Aldo André, and Paulo R. G. Kurka. "Computer vision methods for automotive applications." TECNIA 30, no. 2 (2020): 74–81. http://dx.doi.org/10.21754/tecnia.v30i2.801.

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Recent advances in computer vision have favored technological developments in the automotive industry. In this work, we present methods relevant to the use of cameras as measurement devices in computer vision and their applications in the automotive industry. The methods are edge and ellipse detection, camera calibration, 3-D reconstruction and stereo vision. The applications include methods for detecting rims in automotive wheels, estimation of the calibration angles of vehicles and the reconstruction of a vehicle's trajectory using stereo vision. The results showed the potential of computer

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Ramezani Dooraki, Amir. "A survey on computer vision technology in Camera Based ETA devices." International Journal of Advances in Intelligent Informatics 1, no. 3 (2015): 115. http://dx.doi.org/10.26555/ijain.v1i3.40.

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Electronic Travel Aid systems are expected to make impaired persons able to perform their everyday tasks such as finding an object and avoiding obstacles easier. Among ETA devices, Camera Based ETA devices are the new one and with a high potential for helping Visually Impaired Persons. With recent advances in computer science and specially computer vision, Camera Based ETA devices used several computer vision algorithms and techniques such as object recognition and stereo vision in order to help VIP to perform tasks such as reading banknotes, recognizing people and avoiding obstacles. This pap

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Wan, Bin Bin, Tao Zheng Zhang, Jian Ping Chai, and Fu Lian Yin. "Research of User Experience and Data Mining for Stereo Vision." Applied Mechanics and Materials 457-458 (October 2013): 984–87. http://dx.doi.org/10.4028/www.scientific.net/amm.457-458.984.

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With the development of integration of three networks which combines telecommunication network, computer network and cable television network [1-2], decision support system for stereo vision is proposed. Combined with the user experience which is given a model of the influence factor in this paper of Stereo vision, the data mining model will be more comprehensive and more convincing and the decision support system for stereo vision will be more plump and more practical. This paper designs the model of the influence factor for Stereo vision user experience which makes the data mining model for

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Woodfill, John Iselin, Ron Buck, Dave Jurasek, Gaile Gordon, and Terrance Brown. "3D Vision: Developing an Embedded Stereo-Vision System." Computer 40, no. 5 (2007): 106–8. http://dx.doi.org/10.1109/mc.2007.151.

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6

Reimann, D., and H. Haken. "Stereo vision by self-organization." Biological Cybernetics 71, no. 1 (1994): 17–26. http://dx.doi.org/10.1007/s004220050064.

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Reimann, D., and H. Haken. "Stereo vision by self-organization." Biological Cybernetics 71, no. 1 (1994): 17–26. http://dx.doi.org/10.1007/bf00198908.

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8

Hu, Gan Le, Yan Chen, and Zheng Guo Gu. "Stereo Vision Based Distance Measurement and its Application." Advanced Materials Research 926-930 (May 2014): 3258–61. http://dx.doi.org/10.4028/www.scientific.net/amr.926-930.3258.

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In computer graphics, Stereo Vision has been a research hotspot for many years, and it is been widely used in many areas. Stereo Vision is a technique which utilizes computer to simulate human eye system. In order to achieve this simulation, two main problems need to be solved: camera calibration and stereo matching. We focus on stereo matching in this paper. After years of development some achievements have been made in stereo matching, but some problems remain unsolved. The two most important things concerned in stereo vision trend to be contradictory: accuracy and efficiency. This paper pre

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Pomaska, G. "STEREO VISION APPLYING OPENCV AND RASPBERRY PI." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W17 (November 29, 2019): 265–69. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w17-265-2019.

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Abstract. This article points out the single board computer Raspberry Pi and the related camera modules for image acquisition. Particular attention is directed to stereoscopic image recording and post processing software applying OpenCV. A design of a camera network is created and applied to a field application. The OpenCV computer vision library and its Python binding provides some script samples to encourage users developing their own custom tailored scripts. Stereoscopic recording is intended for extended base lines without a mechanical bar. Image series will be taken in order to wipe out m

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Lu, Luanhao. "A Survey of Learning Approaches and Application for 3D Vision." MATEC Web of Conferences 173 (2018): 03053. http://dx.doi.org/10.1051/matecconf/201817303053.

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Three-dimensional (3D) vision extracted from the stereo images or reconstructed from the two-dimensional (2D) images is the most effective topic in computer vision and video surveillance. Three-dimensional scene is constructed through two stereo images which existing disparity map by Stereo vision. Many methods of Stereo matching which contains median filtering, mean-shift segmentation, guided filter and joint trilateral filters [1] are used in many algorithms to construct the precise disparity map. These methods committed to figure out the image synthesis range in different Stereo matching fi

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Baek, Seung-Hae, Pathum Rathnayaka, and Soon-Yong Park. "Calibration of a Stereo Radiation Detection Camera Using Planar Homography." Journal of Sensors 2016 (2016): 1–11. http://dx.doi.org/10.1155/2016/8928096.

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This paper proposes a calibration technique of a stereo gamma detection camera. Calibration of the internal and external parameters of a stereo vision camera is a well-known research problem in the computer vision society. However, few or no stereo calibration has been investigated in the radiation measurement research. Since no visual information can be obtained from a stereo radiation camera, it is impossible to use a general stereo calibration algorithm directly. In this paper, we develop a hybrid-type stereo system which is equipped with both radiation and vision cameras. To calibrate the

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12

Sugihara, Kokichi. "Three principles in stereo vision." Advanced Robotics 1, no. 4 (1986): 391–400. http://dx.doi.org/10.1163/156855386x00256.

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13

Martinez-de Dios, J. R., C. Serna, and A. Ollero. "Computer vision and robotics techniques in fish farms." Robotica 21, no. 3 (2003): 233–43. http://dx.doi.org/10.1017/s0263574702004733.

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This paper presents new low-cost systems for the automation of some fish farm operations. Particularly, computer vision is applied to non-contact fish weight estimation. Stereo vision systems with synchronised convergent cameras are employed to perform fish 3-D segmentation in tanks and sea cages. Several pre-processing algorithms are applied to compensate for illumination local variations. The approach applied for fish 3-D segmentation consists in detecting in both images certain fish features. Once these points have been detected and validated in both images, the fish are 3-D segmented by ap

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14

Ambrosch, Kristian, and Wilfried Kubinger. "Accurate hardware-based stereo vision." Computer Vision and Image Understanding 114, no. 11 (2010): 1303–16. http://dx.doi.org/10.1016/j.cviu.2010.07.008.

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15

Yong, Ho-joong, Jongwon Back, and Tae-Jeong Jang. "Stereo-Vision-Based Human-Computer Interaction with Tactile Stimulation." ETRI Journal 29, no. 3 (2007): 305–10. http://dx.doi.org/10.4218/etrij.07.0506.0017.

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16

Prokopchuk, Oleh, and Serhii Vovk. "Application of morphological processing methods in computer stereo vision." System technologies 6, no. 131 (2021): 18–27. http://dx.doi.org/10.34185/1562-9945-6-131-2020-03.

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Computer vision algorithms are important for many areas of human activity. In particular, the number of applications related to the need to process images of real-world objects with computerized tools and the subsequent use of descriptive information in a variety of interactive and automated decision-making systems is increased. An important tool for analyzing real-world scenes are approaches to the application of stereo vision algorithms. The important step of many stereo matching algorithms is a disparity map. Depending on the content of the observed scene, part of the values on the disparit

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17

Ma, Wen Juan, Shu Sen Sun, Jin Yu Song, and Wen Shu Li. "Circle Pose Estimation Based on Stereo Vision." Applied Mechanics and Materials 263-266 (December 2012): 2408–13. http://dx.doi.org/10.4028/www.scientific.net/amm.263-266.2408.

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This paper presents a simple method of circle pose estimation based on binocular stereo vision. It takes the projective equation of a circle as the basis, and gives the closed form solution of the pose parameters. Since there are two possible sets of pose parameters for a circle from one calibrated perspective view, the stereo vision constraints are incorporated and the accurate pose parameters are determined. Experiments using computer simulated data and real data demonstrate the robustness and accuracy of our method.

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Liu, J., S. Ji, C. Zhang, and Z. Qin. "EVALUATION OF DEEP LEARNING BASED STEREO MATCHING METHODS: FROM GROUND TO AERIAL IMAGES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2 (May 30, 2018): 593–97. http://dx.doi.org/10.5194/isprs-archives-xlii-2-593-2018.

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Dense stereo matching has been extensively studied in photogrammetry and computer vision. In this paper we evaluate the application of deep learning based stereo methods, which were raised from 2016 and rapidly spread, on aerial stereos other than ground images that are commonly used in computer vision community. Two popular methods are evaluated. One learns matching cost with a convolutional neural network (known as MC-CNN); the other produces a disparity map in an end-to-end manner by utilizing both geometry and context (known as GC-net). First, we evaluate the performance of the deep learni

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19

Li, Yan Yun, Zhao Hui Liu, and Liang Zhou. "Analysis and Research of Stereo Correspondence Algorithms." Applied Mechanics and Materials 568-570 (June 2014): 768–72. http://dx.doi.org/10.4028/www.scientific.net/amm.568-570.768.

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Stereo matching has been the focus of computer vision research. Some current researches on stereo matching algorithms were summarized, the stereo matching key techniques were analyzed; View of the current major challenges on binocular stereo matching, elaborated matching algorithm possible solutions and modification approaches; Finally, the field of technology development are prospected.

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Dan, Hua Zhi, and Bernard Dubuisson. "String matching for stereo vision." Pattern Recognition Letters 9, no. 2 (1989): 117–26. http://dx.doi.org/10.1016/0167-8655(89)90044-5.

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Martín, S., J. Suárez, R. Orea, R. Rubio, and R. Gallego. "GLSV: Graphics library stereo vision for OpenGL." Virtual Reality 13, no. 1 (2008): 51–57. http://dx.doi.org/10.1007/s10055-008-0105-y.

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22

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 (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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23

Jiang, Yan, and Jian Tang. "Application of 3D Stereo Visualization System in Virtual Architectural Design." Applied Mechanics and Materials 174-177 (May 2012): 1706–9. http://dx.doi.org/10.4028/www.scientific.net/amm.174-177.1706.

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The application of virtual reality in architectural design has been the focus of attention. But the true 3D sense of immersion is still a dream for the most designers and clients when they watch the computer screen. A new computer stereo vision imaging system was constructed to help us obtain 3D visual of architectures and the implementation process became easier. And the application of advanced three-dimensional vision technology offered a more scientific, more interesting means of display and human-computer interaction. By using 3D stereo vision imaging system, all designers and users can ob

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24

Dominguez-Morales, Manuel J., Angel Jimenez-Fernandez, Gabriel Jimenez-Moreno, Cristina Conde, Enrique Cabello, and Alejandro Linares-Barranco. "Bio-Inspired Stereo Vision Calibration for Dynamic Vision Sensors." IEEE Access 7 (2019): 138415–25. http://dx.doi.org/10.1109/access.2019.2943160.

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25

Rovira-Más, Francisco, Qi Wang, and Qin Zhang. "Bifocal Stereoscopic Vision for Intelligent Vehicles." International Journal of Vehicular Technology 2009 (March 29, 2009): 1–9. http://dx.doi.org/10.1155/2009/123231.

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The numerous benefits of real-time 3D awareness for autonomous vehicles have motivated the incorporation of stereo cameras to the perception units of intelligent vehicles. The availability of the distance between camera and objects is essential for such applications as automatic guidance and safeguarding; however, a poor estimation of the position of the objects in front of the vehicle can result in dangerous actions. There is an emphasis, therefore, in the design of perception engines that can make available a rich and reliable interval of ranges in front of the camera. The objective of this

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Zoppi, Matteo, and Rezia Molfino. "ArmillEye: Flexible Platform for Underwater Stereo Vision." Journal of Mechanical Design 129, no. 8 (2006): 808–15. http://dx.doi.org/10.1115/1.2735338.

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The paper describes ArmillEye, a 3-degree of freedom (DOF) flexible hybrid platform designed for agile underwater stereoptic vision. Effective telecontrol systems of remote operated vehicles require active and dexterous camera support in order to allow the operator to easily and promptly change the point of view, also improving the virtual reconstruction of the environment in difficult operative conditions (dirtiness, turbulence, and partial occlusion). The same concepts hold for visual servoing of autonomous underwater vehicles. ArmillEye was designed for this specific application; it is base

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Ramírez-Hernández, Luis R., Julio C. Rodríguez-Quiñonez, Moises J. Castro-Toscano, et al. "Improve three-dimensional point localization accuracy in stereo vision systems using a novel camera calibration method." International Journal of Advanced Robotic Systems 17, no. 1 (2020): 172988141989671. http://dx.doi.org/10.1177/1729881419896717.

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Computer vision systems have demonstrated to be useful in applications of autonomous navigation, especially with the use of stereo vision systems for the three-dimensional mapping of the environment. This article presents a novel camera calibration method to improve the accuracy of stereo vision systems for three-dimensional point localization. The proposed camera calibration method uses the least square method to model the error caused by the image digitalization and the lens distortion. To obtain particular three-dimensional point coordinates, the stereo vision systems use the information of

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PRETLOVE, J. R. G., and G. A. PARKER. "THE SURREY ATTENTIVE ROBOT VISION SYSTEM." International Journal of Pattern Recognition and Artificial Intelligence 07, no. 01 (1993): 89–107. http://dx.doi.org/10.1142/s0218001493000066.

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This paper presents the design and development of a real-time eye-in-hand stereo-vision system to aid robot guidance in a manufacturing environment. The stereo vision head comprises a novel camera arrangement with servo-vergence, focus, and aperture that continuously provides high-quality images to a dedicated image processing system and parallel processing array. The stereo head has four degrees of freedom but it relies on the robot end-effector for all remaining movement. This provides the robot with exploratory sensing abilities allowing it to undertake a wider variety of less constrained t

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Sharma, Kajal. "GPU Optimized Stereo Image Matching Technique for Computer Vision Applications." International Journal of Modern Education and Computer Science 7, no. 5 (2015): 37–42. http://dx.doi.org/10.5815/ijmecs.2015.05.05.

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Zhao, Lei. "Research on Virtual Piano Based on Computer Binocular Stereo Vision." Journal of Physics: Conference Series 1533 (April 2020): 032006. http://dx.doi.org/10.1088/1742-6596/1533/3/032006.

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Gimel'farb, G. L. "Intensity-based computer binocular stereo vision: Signal models and algorithms." International Journal of Imaging Systems and Technology 3, no. 3 (1991): 189–200. http://dx.doi.org/10.1002/ima.1850030304.

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Kalmari, Jouko, Jakke Kulovesi, and Arto Visala. "Measuring Log Length using Computer Stereo Vision in Harvester Head." IFAC Proceedings Volumes 44, no. 1 (2011): 2226–29. http://dx.doi.org/10.3182/20110828-6-it-1002.03498.

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EKLUND, MATTHEW P., ALY A. FARAG, and MOUMEN T. EL-MELEGY. "ROBUST CORRESPONDENCE METHODS FOR STEREO VISION." International Journal of Pattern Recognition and Artificial Intelligence 17, no. 07 (2003): 1059–79. http://dx.doi.org/10.1142/s0218001403002861.

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Correspondence is one of the major problems that must be solved in stereo vision. Correlation has been commonly used in the past for this problem. However, most classical linear correlation methods fail near depth discontinuities and in the presence of occlusions. Many robust methods have been proposed that claim to effectively deal with some or all of these issues. Many of these robust methods are transformation-based, however, other robust methods are non-transformation based. This paper gives five requirements that should be met by a transformation-based robust correlation method. We compar

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Wan, Dingrui, and Jie Zhou. "Stereo vision using two PTZ cameras." Computer Vision and Image Understanding 112, no. 2 (2008): 184–94. http://dx.doi.org/10.1016/j.cviu.2008.02.005.

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Belyakov, P. V., M. B. Nikiforov, E. R. Muratov, and O. V. Melnik. "Stereo vision-based variational optical flow estimation." E3S Web of Conferences 224 (2020): 01027. http://dx.doi.org/10.1051/e3sconf/202022401027.

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Optical flow computation is one of the most important tasks in computer vision. The article deals with a modification of the variational method of the optical flow computation, according to its application in stereo vision. Such approaches are traditionally based on a brightness constancy assumption and a gradient constancy assumption during pixels motion. Smoothness assumption also restricts motion discontinuities, i.e. the smoothness of the vector field of pixel velocity is assumed. It is proposed to extend the functional of the optical flow computation in a similar way by adding a priori kn

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Zou, Xiang Jun, Hai Xin Zou, J. Lu, et al. "Research on Manipulator Positioning Based on Stereo Vision in Virtual Environment." Key Engineering Materials 392-394 (October 2008): 200–204. http://dx.doi.org/10.4028/www.scientific.net/kem.392-394.200.

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Inherent uncertainties always exist in the positioning picking manipulators in complex environment, modeling and simulation of positioning. The manipulators were discussed based on binocular stereo vision in virtual environment (VE). Based on stereo vision, a method how virtual manipulators locate picking object by human-computer interaction (HCI) was proposed. The data input from vision were mapped to virtual picking manipulators so that it could enable the positioning and simulation with route and events-driven mechanism. The positioning experimental platform in VE consists of hardware of CC

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Pong, Ting-Chuen, Robert M. Haralick, and Linda G. Shapiro. "Matching topographic structures in stereo vision." Pattern Recognition Letters 9, no. 2 (1989): 127–36. http://dx.doi.org/10.1016/0167-8655(89)90045-7.

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Sagara, Shinichi, Radzi Bin Ambar, and Fumiaki Takemura. "A Stereo Vision System for Underwater Vehicle-Manipulator Systems – Proposal of a Novel Concept Using Pan-Tilt-Slide Cameras –." Journal of Robotics and Mechatronics 25, no. 5 (2013): 785–94. http://dx.doi.org/10.20965/jrm.2013.p0785.

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Underwater Vehicle-Manipulator Systems (UVMS) are expected to be used in various tasks in underwater environments. The manipulators of the UVMS are designed to execute tasks such as handling and catching objects. It is therefore necessary to equip UVMS with sensors that observe and measure the position of target objects. Stereo vision systems are one type of such sensors. We propose a stereo vision system for UVMS consisting of 2 mobile cameras that pan, tilt and slide individually using motors. This vision system is installed inside a waterproof cylindrical container that enables it to track

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Olson, Clark F., and Habib Abi-Rached. "Wide-baseline stereo vision for terrain mapping." Machine Vision and Applications 21, no. 5 (2009): 713–25. http://dx.doi.org/10.1007/s00138-009-0188-9.

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Mulligan, Jane. "Fast Calibrated Stereo Vision for Manipulation." Real-Time Imaging 3, no. 5 (1997): 331–41. http://dx.doi.org/10.1006/rtim.1996.0068.

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Liu, Renwei, Zhiyuan Wang, Todd Sparks, Frank Liou, and Cedo Nedic. "Stereo vision-based repair of metallic components." Rapid Prototyping Journal 23, no. 1 (2017): 65–73. http://dx.doi.org/10.1108/rpj-09-2015-0118.

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Purpose This paper aims to investigate a stereo vision-based hybrid (additive and subtractive) manufacturing process using direct laser metal deposition, computer numerical control (CNC) machining and in-process scanning to repair metallic components automatically. The focus of this work was to realize automated alignment and adaptive tool path generation that can repair metallic components after a single setup. Design/methodology/approach Stereo vision was used to detect the defect area for automated alignment. After the defect is located, a laser displacement sensor is used to scan the defec

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

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

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Xiong, Weihua, and Brian Funt. "Stereo retinex." Image and Vision Computing 27, no. 1-2 (2009): 178–88. http://dx.doi.org/10.1016/j.imavis.2007.11.012.

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Mansour, Mostafa, Pavel Davidson, Oleg Stepanov, and Robert Piché. "Relative Importance of Binocular Disparity and Motion Parallax for Depth Estimation: A Computer Vision Approach." Remote Sensing 11, no. 17 (2019): 1990. http://dx.doi.org/10.3390/rs11171990.

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Binocular disparity and motion parallax are the most important cues for depth estimation in human and computer vision. Here, we present an experimental study to evaluate the accuracy of these two cues in depth estimation to stationary objects in a static environment. Depth estimation via binocular disparity is most commonly implemented using stereo vision, which uses images from two or more cameras to triangulate and estimate distances. We use a commercial stereo camera mounted on a wheeled robot to create a depth map of the environment. The sequence of images obtained by one of these two came

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Mu, Zhen-Hai. "3D Reconstruction Algorithm of Weld Pool Surface Based on Computer Vision Technology." Open Mechanical Engineering Journal 9, no. 1 (2015): 820–25. http://dx.doi.org/10.2174/1874155x01509010820.

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As is well known that sensing and measuring the weld pool surface is very important to design intelligent welding machines which is able to imitate a skilled human welder who can choose suitable welding parameters. Therefore, in this paper, we focused on the problem of weld pool surface 3D reconstruction, which is a key issue in intelligent welding machines development. Firstly, the framework of the weld pool surface 3D reconstruction system is described. The weld pool surface 3D reconstruction system uses a single camera stereo vision system to extract original data from weld pool, and then t

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Liu, X., and K. Fujimura. "Pedestrian Detection Using Stereo Night Vision." IEEE Transactions on Vehicular Technology 53, no. 6 (2004): 1657–65. http://dx.doi.org/10.1109/tvt.2004.834876.

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Yang, Yingpeng. "A Stereo Matching System." International Journal of Advanced Pervasive and Ubiquitous Computing 5, no. 2 (2013): 1–8. http://dx.doi.org/10.4018/japuc.2013040101.

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Determination of the depth of the image feature distinctive automation and other industries of machine vision and computer vision technology in everyday life are becoming increasingly popular. Some techniques have been proposed to extract from the current depth of a 2D image of the feature, which defines a particular object or structure of the information. In many cases, these techniques are automatic, such as a suitable carrier moving average depth identify objects placed in the 2D image. For this intensive depth cues to solve two stereo matching algorithm using a machine learning algorithm.

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Jin, Minxi, and Tsutomu Maruyama. "Fast and Accurate Stereo Vision System on FPGA." ACM Transactions on Reconfigurable Technology and Systems 7, no. 1 (2014): 1–24. http://dx.doi.org/10.1145/2567659.

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

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Based on analyzing current methods of acquiring point clouds data in reversing engineering, considering the features of structure light scanning and binocular stereovision, we proposed a composite measuring method based on vision technology, which combines the advantages of the two measurement methods in together, and established the measuring system. The greatest advantage of this method is that the edge data were obtained by binocular vision technology, and the internal data were obtained by Structure light method. In binocular vision, stereo matching was realized with the combination of epi

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Zhu, Jigui. "STUDY ON SINGLE CAMERA STEREO VISION SENSOR." Chinese Journal of Mechanical Engineering 41, no. 12 (2005): 151. http://dx.doi.org/10.3901/jme.2005.12.151.

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