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Journal articles on the topic 'Camera Projector Calibration'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

Motta, Thiago, Manuel Loaiza, Alberto Raposo, and Luciano Soares. "Kinect Projection Mapping." Journal on Interactive Systems 5, no. 3 (December 30, 2014): 1. http://dx.doi.org/10.5753/jis.2014.722.

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Spatial augmented reality allows users to create a projected virtual environment on irregular surfaces. This demands an accurate Camera-Projector calibration process in order to produce precise 3D information to match the real object. This paper presents a framework to process data achieved from a calibration of a Kinect-Projector system in visualization applications, allowing the user to create an augmented reality environment without having extensive process of the Camera-Projector calibration, while maintaining a precise calibration to the projection on irregular surfaces. Additionally, different calibration techniques were evaluated in order to demonstrate the better approaches.

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2

Yakno, Marlina, Junita Mohamad-Saleh, Mohd Zamri Ibrahim, and W. N. A. W. Samsudin. "Camera-projector calibration for near infrared imaging system." Bulletin of Electrical Engineering and Informatics 9, no. 1 (February 1, 2020): 160–70. http://dx.doi.org/10.11591/eei.v9i1.1697.

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Advanced biomedical engineering technologies are continuously changing the medical practices to improve medical care for patients. Needle insertion navigation during intravenous catheterization process via Near infrared (NIR) and camera-projector is one solution. However, the central point of the problem is the image captured by camera misaligns with the image projected back on the object of interest. This causes the projected image not to be overlaid perfectly in the real-world. In this paper, a camera-projector calibration method is presented. Polynomial algorithm was used to remove the barrel distortion in captured images. Scaling and translation transformations are used to correct the geometric distortions introduced in the image acquisition process. Discrepancies in the captured and projected images are assessed. The accuracy of the image and the projected image is 90.643%. This indicates the feasibility of the captured approach to eliminate discrepancies in the projection and navigation images.

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3

Yu, Guang, Bo Yang Yu, Shu Cai Yang, Li Wen, Wen Fei Dong, and Hui Wang. "The Projector Calibration Based on ZHANG’s Self-Calibration Method." Advanced Materials Research 981 (July 2014): 364–67. http://dx.doi.org/10.4028/www.scientific.net/amr.981.364.

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Projector calibration can be seen as a special case of the camera calibration. It can establish the relationship of the three dimensional space coordinates for points and projector image coordinates for points DMD by using a projector to project coding pattern. In camera calibration, ZHANG’s self-calibration was conducted in the maximum likelihood linear refinement. Operation process takes the lens distortion factors into account finding out the camera internal and external parameters finally. Using this algorithm to the projector calibration can solve the traditional linear calibration algorithm which is complex and poor robustness. Otherwise, it can improve the practicability of calibration method. This method can both calibrate the internal and external parameters of projector, which can solve the problem of independently inside or outside calibration.

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4

Zhao, Xue Jin, and Cheng Rui Zhang. "A New Camera and Projector Calibration Method Based on Discrete Computation." Applied Mechanics and Materials 229-231 (November 2012): 1171–75. http://dx.doi.org/10.4028/www.scientific.net/amm.229-231.1171.

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This paper presents a novel method for the calibration of camera and projector based on discrete computation, which uses a linear moving chessboard and project plane to get a calibration database for camera and projector. The camera database contains multi-layers data of the captured chessboard corners and their corresponding practical coordinates in the system. Then by using this database and interpolation algorithm, we can calculate the accurate position for each given pixel position in the captured image. After this we change the chessboard with a white scene and project a chessboard image to the plane. By capturing the projected image and computing the practical position for the corners in the image, we can get a relationship between practical coordinates and the projected image pixels. So another database for the project image and the practical coordinates is established. By using these two databases, we can define the light line for the pixels in a camera captured image and projected image, which can be used for 3D scanning system and other industrial systems, like mask-image projection stereo lithography rapid prototyping system.

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5

Van Crombrugge, Izaak, Rudi Penne, and Steve Vanlanduit. "Extrinsic Camera Calibration with Line-Laser Projection." Sensors 21, no. 4 (February 5, 2021): 1091. http://dx.doi.org/10.3390/s21041091.

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Knowledge of precise camera poses is vital for multi-camera setups. Camera intrinsics can be obtained for each camera separately in lab conditions. For fixed multi-camera setups, the extrinsic calibration can only be done in situ. Usually, some markers are used, like checkerboards, requiring some level of overlap between cameras. In this work, we propose a method for cases with little or no overlap. Laser lines are projected on a plane (e.g., floor or wall) using a laser line projector. The pose of the plane and cameras is then optimized using bundle adjustment to match the lines seen by the cameras. To find the extrinsic calibration, only a partial overlap between the laser lines and the field of view of the cameras is needed. Real-world experiments were conducted both with and without overlapping fields of view, resulting in rotation errors below 0.5°. We show that the accuracy is comparable to other state-of-the-art methods while offering a more practical procedure. The method can also be used in large-scale applications and can be fully automated.

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6

Li, Wen Guo, and Shao Jun Duan. "Convenient Calibration Procedure for Structured Light Projection System." Advanced Materials Research 662 (February 2013): 777–80. http://dx.doi.org/10.4028/www.scientific.net/amr.662.777.

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We present a convenient calibration method for structured light projection system. The proposed clibration approach can realize 3D shape measurement without projector calibration, without system calibration, without precise linear z stage to be used, the relative position between camera and projector can be arbitrary, and the only involved device is a plane board. Experiment results validated that the accuracy of the proposed approach.

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7

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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8

Yu, Xiao Yang, Xiao Liang Meng, Hai Bin Wu, Xiao Ming Sun, and Li Wang. "Coded-Structured Light System Calibration Using Orthogonal Phase Shift Coding Combined with Zhang’s Method." Advanced Materials Research 981 (July 2014): 348–51. http://dx.doi.org/10.4028/www.scientific.net/amr.981.348.

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In coded-structured light three dimensional system, system calibration plays a vital role for the measurement accuracy. The camera calibration method is very mature, but the study about projector calibration is less. Therefore, this paper proposes a projector calibration method with simple calibration process and high accuracy. This method combines the Zhang’?s plane model calibration method with orthogonal phase shift coding. In calibration process, this paper uses phase shift coding pattern to establish the relationship of projector image and camera corner point coordinates. According to the image coordinates in the projector’?s perspective, we program and calculate the projector’?s internal and external parameters matrix based on the Zhang’?s plane model calibration toolbox. The results show that the proposed method is simple and flexible, the maximum relative error of the calibration parameters is 0.03%, and it meets the requirements of system calibration in medical or industrial fields.

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9

Yang, Tao, Yue Liu, and You Lu. "A Rapid Auto-Caliberation Method in Projector-Camera System." Applied Mechanics and Materials 58-60 (June 2011): 2308–13. http://dx.doi.org/10.4028/www.scientific.net/amm.58-60.2308.

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A precise, fast, and fully automatic calibration method is proposed to address the shortcomings in currently used large-scale interactive camera-projector systems. These shortcomings include a small number of calibration points used in manual calibration, large errors, huge time consumption, and lack of professional quality operations. The proposed method applies mechanical wavelength switching in the projected image to capture multi-regional vertices. The co-linearity of each point in the projected images is calculated to determine the actual location of the interactive points in the projected image. The point-by-point computation adopted in the method promotes the automatic elimination of uncorrectable systematic errors in large-scale optical devices. The automatic error elimination not only increases the accuracy of the interactive system and reduces the complexity of system installation, but also increases the flexibility of the interactive system.

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10

Portalés, Cristina, Emilio Ribes-Gómez, Begoña Pastor, and Antonio Gutiérrez. "Calibration of a camera-projector monochromatic system." Photogrammetric Record 30, no. 149 (March 2015): 82–99. http://dx.doi.org/10.1111/phor.12094.

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11

Teubl, Fernando, Marcio Cabral, Marcelo Zuffo, and Celso Kurashima. "Analysis of a Scalable Multi-Projector System for Virtual Reality Environments." International Journal of Virtual Reality 12, no. 1 (January 1, 2013): 15–29. http://dx.doi.org/10.20870/ijvr.2013.12.1.2855.

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Virtual reality environments with multi-projector systems provide better visual quality, higher resolution and more brightness than traditional single-projector systems. Moreover, using multiple low-cost projectors is economically advantageous in comparison to an expensive high-end projector for equivalent visual performance. This article presents the research and development of a scalable multiprojection system that enables the construction of virtual reality systems with a large number of projectors and graphics computers, and that is capable of achieving a high resolution display. We demonstrate the viability of such system with the development of a camera-based multiprojector system library called FastFusion, which automatically calibrates casually aligned projectors to properly blend different projections. Our system software improves known algorithms in the literature for projector calibration and image blending. As a result, FastFusion improves system scalability and calibration reliability. In a detailed analysis of the visual performance of FastFusion in a CAVE system with three walls, eighteen projectors and nine computers, we achieved a satisfactory result for variance in geometric calibration and for graphics performance. Thus, our library is suitable for building complex projector systems and with retina resolution.

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12

Chen, Jian, Ke Tian Li, Xiang Bo Ouyang, and Shao Hua Ding. "The 3D Measuring Method Based on the Color Coding Grating." Applied Mechanics and Materials 109 (October 2011): 385–89. http://dx.doi.org/10.4028/www.scientific.net/amm.109.385.

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This paper puts forward a new method of 3D measurement which based on the color coding structure light technology, projects the specific color coding grating to a Calibration board in RGB three color space, gets the straight line equation of grating which projected to Calibration board in the world coordinate system, obtains each projection plane of code through plane fitting, then joins the projection planes and the object imaging straight strips which through the camera focus, it can be get that the three dimensional coordinates of the objects. This method is simple and reliable; only need one camera and one projector without scanning; only one image is needed to get the information of a full frame depth image. It is suitable for high speed, real-time online measurement.

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13

Liu, Haibo, Huijing Lin, and Linshen Yao. "Calibration method for projector-camera-based telecentric fringe projection profilometry system." Optics Express 25, no. 25 (December 4, 2017): 31492. http://dx.doi.org/10.1364/oe.25.031492.

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14

Deglint, Jason, Andrew Cameron, Christian Scharfenberger, Hicham Sekkati, Mark Lamm, Alexander Wong, and David A. Clausi. "Auto-calibration of a projector-camera stereo system for projection mapping." Journal of the Society for Information Display 24, no. 8 (August 2016): 510–20. http://dx.doi.org/10.1002/jsid.464.

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15

Juarez-Salazar, Rigoberto, and Victor H. Diaz-Ramirez. "Flexible camera-projector calibration using superposed color checkerboards." Optics and Lasers in Engineering 120 (September 2019): 59–65. http://dx.doi.org/10.1016/j.optlaseng.2019.02.016.

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16

Arnold, Katherine, Mohamed A. Naiel, Mark Lamm, and Paul Fieguth. "Evaluation of Solving Methods for the Fundamental Matrix Computation." Journal of Computational Vision and Imaging Systems 6, no. 1 (January 15, 2021): 1. http://dx.doi.org/10.15353/jcvis.v6i1.3563.

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Solving the fundamental matrix is a key step in many image calibration and 3D reconstruction systems. The goal of this paper is to study the performance of non-linear solvers for estimating the fundamental matrix in projector-camera calibration. To prevent measurements errors from distorting our understanding, synthetic data are created from ground-truth camera and projector parameters and then used for the assessment of four nonlinear solving strategies.

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17

Gelšvartas, Julius, Rimvydas Simutis, and Rytis Maskeliūnas. "Projection Mapping User Interface for Disabled People." Journal of Healthcare Engineering 2018 (2018): 1–6. http://dx.doi.org/10.1155/2018/6916204.

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Difficulty in communicating is one of the key challenges for people suffering from severe motor and speech disabilities. Often such person can communicate and interact with the environment only using assistive technologies. This paper presents a multifunctional user interface designed to improve communication efficiency and person independence. The main component of this interface is a projection mapping technique used to highlight objects in the environment. Projection mapping makes it possible to create a natural augmented reality information presentation method. The user interface combines a depth sensor and a projector to create camera-projector system. We provide a detailed description of camera-projector system calibration procedure. The described system performs tabletop object detection and automatic projection mapping. Multiple user input modalities have been integrated into the multifunctional user interface. Such system can be adapted to the needs of people with various disabilities.

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18

Li, Francis, Hicham Sekkati, Jason Deglint, Christian Scharfenberger, Mark Lamm, David Clausi, John Zelek, and Alexander Wong. "Simultaneous Projector-Camera Self-Calibration for Three-Dimensional Reconstruction and Projection Mapping." IEEE Transactions on Computational Imaging 3, no. 1 (March 2017): 74–83. http://dx.doi.org/10.1109/tci.2017.2652844.

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19

Tiscareño, Julieta, José A. Albajez, and Jorge Santolaria. "Analysis of different camera calibration methods on a camera-projector measuring system." Procedia Manufacturing 41 (2019): 539–46. http://dx.doi.org/10.1016/j.promfg.2019.09.041.

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20

Bleier, M., and A. Nüchter. "LOW-COST 3D LASER SCANNING IN AIR ORWATER USING SELF-CALIBRATING STRUCTURED LIGHT." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W3 (February 23, 2017): 105–12. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w3-105-2017.

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In-situ calibration of structured light scanners in underwater environments is time-consuming and complicated. This paper presents a self-calibrating line laser scanning system, which enables the creation of dense 3D models with a single fixed camera and a freely moving hand-held cross line laser projector. The proposed approach exploits geometric constraints, such as coplanarities, to recover the depth information and is applicable without any prior knowledge of the position and orientation of the laser projector. By employing an off-the-shelf underwater camera and a waterproof housing with high power line lasers an affordable 3D scanning solution can be built. In experiments the performance of the proposed technique is studied and compared with 3D reconstruction using explicit calibration. We demonstrate that the scanning system can be applied to above-the-water as well as underwater scenes.

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21

Zhang, Xu. "Projector calibration from the camera image point of view." Optical Engineering 48, no. 11 (November 1, 2009): 117208. http://dx.doi.org/10.1117/1.3265551.

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22

NAKAYAMA, Seiichiro, and Tsuyoshi SHIMIZU. "201 Camera and Projector Calibration Based on Projective Invariants." Proceedings of Yamanashi District Conference 2014 (2014): 29–30. http://dx.doi.org/10.1299/jsmeyamanashi.2014.29.

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23

Chen, Xiaobo, Juntong Xi, Ye Jin, and Jin Sun. "Accurate calibration for a camera–projector measurement system based on structured light projection." Optics and Lasers in Engineering 47, no. 3-4 (March 2009): 310–19. http://dx.doi.org/10.1016/j.optlaseng.2007.12.001.

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24

Wenhai Zou, 邹文海, and 徐海松 Haisong Xu. "A robust photometric calibration framework for projector-camera display system." Chinese Optics Letters 7, no. 6 (2009): 479–82. http://dx.doi.org/10.3788/col20090706.0479.

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25

Zhu, Zhenmin, Sheng Wang, Hailiang Zhang, and Fumin Zhang. "Camera–projector system calibration method based on optimal polarization angle." Optical Engineering 59, no. 03 (March 26, 2020): 1. http://dx.doi.org/10.1117/1.oe.59.3.035104.

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26

Huang, Shujun, Lili Xie, Zhangying Wang, Zonghua Zhang, Feng Gao, and Xiangqian Jiang. "Accurate projector calibration method by using an optical coaxial camera." Applied Optics 54, no. 4 (January 26, 2015): 789. http://dx.doi.org/10.1364/ao.54.000789.

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27

SHIMIZU, Tsuyoshi, Yasutake HARAMIISHI, Nobuyuki FURUYA, Shigeki TOYAMA, and Makoto OBI. "Calibration of Camera and Projector Systems based on Projective Reconstruction." Journal of the Japan Society for Precision Engineering 75, no. 8 (2009): 1005–9. http://dx.doi.org/10.2493/jjspe.75.1005.

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28

Bleier, M., and A. Nüchter. "TOWARDS ROBUST SELF-CALIBRATION FOR HANDHELD 3D LINE LASER SCANNING." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W8 (November 13, 2017): 31–36. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w8-31-2017.

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This paper studies self-calibration of a structured light system, which reconstructs 3D information using video from a static consumer camera and a handheld cross line laser projector. Intersections between the individual laser curves and geometric constraints on the relative position of the laser planes are exploited to achieve dense 3D reconstruction. This is possible without any prior knowledge of the movement of the projector. However, inaccurrately extracted laser lines introduce noise in the detected intersection positions and therefore distort the reconstruction result. Furthermore, when scanning objects with specular reflections, such as glossy painted or metalic surfaces, the reflections are often extracted from the camera image as erroneous laser curves. In this paper we investiagte how robust estimates of the parameters of the laser planes can be obtained despite of noisy detections.

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29

Han, JungSoo, Huicong Wang, Jaiyoung Ryu, and Bruce Rowen. "A Technique for Calibrating Measurements From Photographs of Sliced Specimens." Journal of Biomechanical Engineering 117, no. 4 (November 1, 1995): 495–97. http://dx.doi.org/10.1115/1.2794214.

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Determining the geometry of articular joint surfaces is critical to the study of human joint mechanics. Photographs of sliced specimens (PSS) is currently one of the most popular methods used to determine surface geometry. This study sought to improve the photographs of sliced specimens method through a new calibration technique that includes a mathematical model and a precise plastic grating (calibration grid). Simulations showed that calibration results for x and y coordinates using the new technique attained a high degree of accuracy that was independent of camera and projector lens quality, degree of parallelity between the projector and digitizing table and selection of the area to be calibrated.

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30

Huang, Junhui, Zhao Wang, Qi Xue, and Jianmin Gao. "Calibration of a camera–projector measurement system and error impact analysis." Measurement Science and Technology 23, no. 12 (October 23, 2012): 125402. http://dx.doi.org/10.1088/0957-0233/23/12/125402.

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31

Gao, Yuan, Yuyun Zhao, Le Xie, and Guoyan Zheng. "A Projector-Based Augmented Reality Navigation System for Computer-Assisted Surgery." Sensors 21, no. 9 (April 22, 2021): 2931. http://dx.doi.org/10.3390/s21092931.

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In the medical field, guidance to follow the surgical plan is crucial. Image overlay projection is a solution to link the surgical plan with the patient. It realizes augmented reality (AR) by projecting computer-generated image on the surface of the target through a projector, which can visualize additional information to the scene. By overlaying anatomical information or surgical plans on the surgery area, projection helps to enhance the surgeon’s understanding of the anatomical structure, and intuitively visualizes the surgical target and key structures of the operation, and avoid the surgeon’s sight diversion between monitor and patient. However, it still remains a challenge to project the surgical navigation information on the target precisely and efficiently. In this study, we propose a projector-based surgical navigation system. Through the gray code-based calibration method, the projector can be calibrated with a camera and then be integrated with an optical spatial locator, so that the navigation information of the operation can be accurately projected onto the target area. We validated the projection accuracy of the system through back projection, with average projection error of 3.37 pixels in x direction and 1.51 pixels in y direction, and model projection with an average position error of 1.03 ± 0.43 mm, and carried out puncture experiments using the system with correct rate of 99%, and qualitatively analyzed the system’s performance through the questionnaire. The results demonstrate the efficacy of our proposed AR system.

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32

Sardemann, H., C. Mulsow, and H. G. Maas. "STRICT GEOMETRIC CALIBRATION OF AN UNDERWATER LASER TRIANGULATION SYSTEM." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B2-2021 (June 28, 2021): 689–92. http://dx.doi.org/10.5194/isprs-archives-xliii-b2-2021-689-2021.

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Abstract. This paper will describe a novel approach for the calibration of an underwater laser triangulation system. Underwater triangulation systems, consisting of a line laser and a camera can be used to determine the geometry of submerged objects or the topography of a water body bottom. Placing camera and laser line projector inside a waterproof housing leads to refraction effects at the air-glass-water interfaces, both of the laser light-sheet and image rays. This implies a deformed laser plane in the water and a curved line on the object surface. The proposed approach strictly models the geometry between camera, laser and housing. First experiments show, that the calibration method can be applied for water depth measurements with accuracies of 0.2–0.3 mm at depths in the order of 100 mm.

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33

Ryu, Byungyong, and Sung-Ho Bae. "Display in the Wild (DIW): An Adaptive Projection-Imaging System to Screen Geometry in Real Time." Sensors 18, no. 9 (September 12, 2018): 3063. http://dx.doi.org/10.3390/s18093063.

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TVs and monitors are among the most widely used displays in various environments. However, they have limitations in their physical display conditions, such as a fixed size/position and a rigid/flat space. In this paper, we suggest a new “Display in the Wild” (DIW) concept to overcome the aforementioned problems. Our proposed DIW system allows us to display a flexibly large screen on dynamic non-planar surfaces at an arbitrary display position. To implement our DIW concept practically, we choose a projector as the hardware configuration in order to generate a screen anywhere with different sizes. However, distortion occurs when the projector displays content on a surface that is dynamic and/or non-planar. Therefore, we propose a distortion correction method for DIW to overcome the aforementioned surface constraints. Since projectors are not capture devices, we propose using a depth camera to determine the distortions on the surfaces quickly. We also propose DIW-specific calibration and fast/precise correction methods. Our calibration method is constructed to detect the projection surface easily and quickly, and also allows our proposed system to accommodate the intrinsic parameters such as a display resolution and field of view. We accomplish a fast undistortion process of the projector by considering only surface boundary pixels, which enables our method to run in real time. In our comprehensive experiments, the proposed DIW system generates undistorted screens such as TVs and monitors on dynamic non-planar surfaces at an arbitrary display position with Unmanned Aerial Vehicles (UAVs) in a fast and accurate manner, demonstrating its usefulness in practical DIW scenarios.

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Park, Soon-Yong, Go-Gwang Park, and Lei Zhang. "An Easy Camera-Projector Calibration Technique for Structured Light 3-D Reconstruction." KIPS Transactions:PartB 17B, no. 3 (June 30, 2010): 215–26. http://dx.doi.org/10.3745/kipstb.2010.17b.3.215.

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Lee, Seokhan, Soowoong Jeong, Haneul Yu, Guisik Kim, Hanoung Kwak, Eunju Kang, and Sangkeun Lee. "Efficient Image Transformation and Camera Registration for the Multi-Projector Image Calibration." TECHART: Journal of Arts and Imaging Science 3, no. 1 (February 29, 2016): 38. http://dx.doi.org/10.15323/techart.2016.02.3.1.38.

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36

Nie, Lei, Yuping Ye, and Zhan Song. "Method for calibration accuracy improvement of projector-camera-based structured light system." Optical Engineering 56, no. 7 (July 4, 2017): 074101. http://dx.doi.org/10.1117/1.oe.56.7.074101.

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37

Liu, Jinbo, Xianguo Yu, Kai Yang, Xinxin Zhu, and Yue Wu. "Automatic calibration method for the full parameter of a camera-projector system." Optical Engineering 58, no. 08 (August 16, 2019): 1. http://dx.doi.org/10.1117/1.oe.58.8.084105.

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38

Chen, Rui, Jing Xu, Heping Chen, Jianhua Su, Zonghua Zhang, and Ken Chen. "Accurate calibration method for camera and projector in fringe patterns measurement system." Applied Optics 55, no. 16 (May 24, 2016): 4293. http://dx.doi.org/10.1364/ao.55.004293.

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39

Feng, Zexi, Zhiquan Cheng, and Zhan Song. "A closed-form single-pose calibration method for the camera–projector system." Machine Vision and Applications 30, no. 3 (January 18, 2019): 461–72. http://dx.doi.org/10.1007/s00138-019-01002-2.

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40

Siriborvornratanakul, Thitirat, and Masanori Sugimoto. "ipProjector: Designs and Techniques for Geometry-Based Interactive Applications Using a Portable Projector." International Journal of Digital Multimedia Broadcasting 2010 (2010): 1–12. http://dx.doi.org/10.1155/2010/352060.

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We propose an interactive projection system for a virtual studio setup using a single self-contained and portable projection device. The system is named ipProjector, which stands for Interactive Portable Projector. Projection allows special effects of a virtual studio to be seen by live audiences in real time. The portable device supports 360-degree shooting and projecting angles and is easy to be integrated with an existing studio setup. We focus on two fundamental requirements of the system and their implementations. First, nonintrusive projection is performed to ensure that the special effect projections and the environment analysis (for locating the target actors or objects) can be performed simultaneously in real time. Our approach uses Digital Light Processing technology, color wheel analysis, and nearest-neighbor search algorithm. Second, a paired projector-camera system is geometrically calibrated with two alternative setups. The first uses a motion sensor for real-time geometric calibration, and the second uses a beam splitter for scene-independent geometric calibration. Based on a small-scale laboratory setting, experiments were conducted to evaluate the geometric accuracy of the proposed approaches, and an application was built to demonstrate the proposed ipProjector concept. Techniques of special effect rendering are not concerned in this paper.

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41

Vargas, R., A. G. Marrugo, J. Pineda, J. Meneses, and L. Romero. "Camera-Projector Calibration Methods with Compensation of Geometric Distortions in Fringe Projection Profilometry: A Comparative Study." Optica Pura y Aplicada 51, no. 3 (October 5, 2018): 1–10. http://dx.doi.org/10.7149/opa.51.3.50305.

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Sauli, Zaliman, Vithyacharan Retnasamy, Nor Shakirina Nadzri, and Christopher John Veriven. "3D Shape Measurement and Reconstruction Using Fringe Projection." Applied Mechanics and Materials 487 (January 2014): 572–75. http://dx.doi.org/10.4028/www.scientific.net/amm.487.572.

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Digital fringe projection technique using phase shifting method has been studied extensively for generatingthree dimensional (3D) surface information. The aim of this paper is to develop a simple automated optical inspection (AOI) system using fringe projection technique to capture image of an object. A three step phase shifting is used to generate the saw tooth image to retrieve the information of the pixel coordinate and surface dimension. The calibration of the camera and projector is observed to contribute a great significant on the measurement accuracy. The developed system is capable to measure the object surface dimension and perform the 3D reconstruction with high speed and good precision.

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Douet, Jules, Jing Xu, and Ken Chen. "Sphere-Based Geometrical Calibration Method for Structured Light Surface Measurement Systems." Advanced Materials Research 571 (September 2012): 433–38. http://dx.doi.org/10.4028/www.scientific.net/amr.571.433.

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This paper proposes a sphere-based calibration method for the structured light system with unconstrained one projector & one camera, regardless of pattern codification. A 1-pose example of such a method is also proposed and tested. In comparison with a traditional plane translation method of 15 poses, we note an increase in the consistency of more than 10% while the calibration time shrinks to 6% and the calibration accessory is reduced to the size of a flash-light. This method suits well for applications where mobility, speed and ease-of-use are important criteria.

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Park, Min Ki, Kyu Je Lim, Myoung Kook Seo, Soon Jong Jung, and Kwan H. Lee. "Spatial augmented reality for product appearance design evaluation." Journal of Computational Design and Engineering 2, no. 1 (December 6, 2014): 38–46. http://dx.doi.org/10.1016/j.jcde.2014.11.004.

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Abstract Augmented reality based on projection, called “Spatial Augmented Reality (SAR)”, is a new technology that can produce immersive contents by overlapping virtuality and real-world environment. It has been paid attention as the next generation digital contents in media art and human–computer interaction (HCI). In this paper, we present a new methodology to evaluate the product appearance design more intuitively by means of SAR technique. The proposed method first projects the high-quality rendered image considering the optical property of materials onto the mock-up of a product. We also conduct a projector-camera calibration to compensate a color distortion according to a projector, a projection surface and environment lighting. The design evaluation methodology we propose offers more flexible and intuitive evaluation environment to a designer and user (evaluator) than previous methods that are performed via a digital display. At the end of this research, we have conducted a case study for designing and evaluating appearance design of an automobile.

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Huang, Zhengrong, Jiangtao Xi, Yanguang Yu, and Qinghua Guo. "Accurate projector calibration based on a new point-to-point mapping relationship between the camera and projector images." Applied Optics 54, no. 3 (January 12, 2015): 347. http://dx.doi.org/10.1364/ao.54.000347.

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Chen, Chia-Yen, and Hsiang-Jen Chien. "An Incremental Target-Adapted Strategy for Active Geometric Calibration of Projector-Camera Systems." Sensors 13, no. 2 (February 22, 2013): 2664–81. http://dx.doi.org/10.3390/s130202664.

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CHIBA, Naoya, and Koichi HASHIMOTO. "Development of Calibration Tool for Projector-Camera System Considering Saturation And Gamma Correction." Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) 2018 (2018): 2A1—M13. http://dx.doi.org/10.1299/jsmermd.2018.2a1-m13.

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Song, Li-mei, Chang-man Chen, Zhuo Chen, Jiang-tao Xi, and Yan-guang Yu. "Essential parameter calibration for the 3D scanner with only single camera and projector." Optoelectronics Letters 9, no. 2 (March 2013): 143–47. http://dx.doi.org/10.1007/s11801-013-2395-x.

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Tran, Van Luan, and Huei-Yung Lin. "A Structured Light RGB-D Camera System for Accurate Depth Measurement." International Journal of Optics 2018 (November 1, 2018): 1–7. http://dx.doi.org/10.1155/2018/8659847.

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The ability to reliably measure the depth of the object surface is very important in a range of high-value industries. With the development of 3D vision techniques, RGB-D cameras have been widely used to perform the 6D pose estimation of target objects for a robotic manipulator. Many applications require accurate shape measurements of the objects for 3D template matching. In this work, we develop an RGB-D camera based on the structured light technique with gray-code coding. The intrinsic and extrinsic parameters of the camera system are determined by a calibration process. 3D reconstruction of the object surface is based on the ray triangulation principle. We construct an RGB-D sensing system with an industrial camera and a digital light projector. In the experiments, real-world objects are used to test the feasibility of the proposed technique. The evaluation carried out using planar objects has demonstrated the accuracy of our RGB-D depth measurement system.

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Li, Wenbin, Yaxin Li, Walid Darwish, Shengjun Tang, Yuling Hu, and Wu Chen. "A Range-Independent Disparity-Based Calibration Model for Structured Light Pattern-Based RGBD Sensor." Sensors 20, no. 3 (January 23, 2020): 639. http://dx.doi.org/10.3390/s20030639.

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Consumer-grade RGBD sensors that provide both colour and depth information have many potential applications, such as robotics control, localization, and mapping, due to their low cost and simple operation. However, the depth measurement provided by consumer-grade RGBD sensors is still inadequate for many high-precision applications, such as rich 3D reconstruction, accurate object recognition and precise localization, due to the fact that the systematic errors of RGB sensors increase exponentially with the ranging distance. Most existing calibration models for depth measurement must be carried out with different distances. In this paper, we reveal the mechanism of how an infrared (IR) camera and IR projector contribute to the overall non-centrosymmetric distortion of a structured light pattern-based RGBD sensor. Then, a new two-step calibration method for RGBD sensors based on the disparity measurement is proposed, which is range-independent and has full frame coverage. Three independent calibration models are used for the calibration for the three main components of the RGBD sensor errors: the infrared camera distortion, the infrared projection distortion, and the infrared cone-caused bias. Experiments show the proposed calibration method can provide precise calibration results in full-range and full-frame coverage of depth measurement. The offset in the edge area of long-range depth (8 m) is reduced from 86 cm to 30 cm, and the relative error is reduced from 11% to 3% of the range distance. Overall, at far range the proposed calibration method can improve the depth accuracy by 70% in the central region of depth frame and 65% in the edge region.

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