Projector calibration from the camera image point of view
01 Nov 2009-Optical Engineering (International Society for Optics and Photonics)-Vol. 48, Iss: 11, pp 117208
TL;DR: This work proposes a method to estimate the projector parameters according to the camera image reprojection error, which does not require us to know the statistical characteristics of the projector image point and makes full use of the background knowledge of the camera images noise.
Abstract: The traditional projector calibration always assumes that the reprojection errors on the projector image are independent and identically distributed and utilize the same method as the camera calibration. Actually, even if the measured points on the camera image are independent and identically distributed Gaussian variables, it is impossible to obtain the statistical characteristics of the reprojection errors on the projector image, because the relation between the original measurement error and the reprojection error is nonlinear. We propose a method to estimate the projector parameters according to the camera image reprojection error. It does not require us to know the statistical characteristics of the projector image point and makes full use of the background knowledge of the camera image noise, because our cost function does not concern the reprojection error on the projector image as is the case in the traditional method. The simulations and experiments affirm that this method has higher precision, even if the real noise is not normal.
Citations
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TL;DR: A review of some of the most used calibration methods for fringe projection profilometry, where both quantitative and qualitative comparative experiments are implemented to show the advantages and constraints of each method.
91 citations
TL;DR: A framework for hyper-accurate system calibration with flexible setup and inexpensive hardware is presented, and the novel FPB 3D imaging technique can achieve a relative measurement accuracy of 0.010%.
Abstract: Fringe-projection-based (FPB) three-dimensional (3D) imaging technique has become one of the most prevalent methods for 3D shape measurement and 3D image acquisition, and an essential component of the technique is the calibration process. This paper presents a framework for hyper-accurate system calibration with flexible setup and inexpensive hardware. Owing to the crucial improvement in the camera calibration technique, an enhanced governing equation for 3D shape determination, and an advanced flexible system calibration technique as well as some practical considerations on accurate fringe phase retrieval, the novel FPB 3D imaging technique can achieve a relative measurement accuracy of 0.010%. The validity and practicality are verified by both simulation and experiments.
91 citations
TL;DR: A technique to cope with the calibration process of Fringe projection profilometry employs a checkerboard along with practical considerations to ensure reliable and accurate calibration.
Abstract: Fringe projection profilometry (FPP) has evolved dramatically, with many highly demanded features for three-dimensional (3D) imaging, such as high accuracy, easy implementation, and capability of measuring multiple objects with complex shapes. A vital component for an FPP-based 3D imaging system is the calibration process. The existing calibration methods lack the ability to be flexibly compatible with various scales of the field of imaging. In this Letter, a technique to cope with this issue is presented; it employs a checkerboard along with practical considerations to ensure reliable and accurate calibration. The validity and practicality of the technique are verified by experiments.
58 citations
TL;DR: Compared with existing approaches based on the direct mapping of the circle centers on the camera image to the projector image, the proposed method is characterized by higher accuracy in mapping the points and thus the projector calibration.
Abstract: The mapping relationship between the charge-coupled device (CCD) of a camera and the digital micro-mirror device (DMD) of a projector, together with the algorithm to estimate the parameters of the projector, determines the accuracy of projector calibration. In this paper, a new method is presented to achieve sub-pixel-level mapping between the camera and projector images. Instead of directly mapping the circle centers from the CCD to the DMD, which is pixel-precision-based, a set of pixels on the circle edge are extracted on the CCD and mapped onto the DMD. The locations of the circle centers are extracted on the DMD by the least-squares fitting technique, thus achieving sub-pixel precision. Compared with existing approaches based on the direct mapping of the circle centers on the camera image to the projector image, the proposed method is characterized by higher accuracy in mapping the points and thus the projector calibration. The experimental results are presented to show the effectiveness of the proposed method in the improvement of the accuracy of the projector calibration.
37 citations
01 Feb 2014
TL;DR: The vanishing points permit to automatically remove the projector’s keystone effect and then to self-calibrate the projector–camera system and the calibration object is a simple planar surface such as a white paper.
Abstract: This paper introduces the vanishing points to self-calibrate a structured light system. The vanishing points permit to automatically remove the projector's keystone effect and then to self-calibrate the projector---camera system. The calibration object is a simple planar surface such as a white paper. Complex patterns and 3D calibrated objects are not required any more. The technique is compared to classic calibration and validated with experimental results.
30 citations
Cites methods from "Projector calibration from the came..."
...The projector models can be divided into three groups [31]: the line model, the light-stripe model and the plane SL model....
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References
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TL;DR: A flexible technique to easily calibrate a camera that only requires the camera to observe a planar pattern shown at a few (at least two) different orientations is proposed and advances 3D computer vision one more step from laboratory environments to real world use.
Abstract: We propose a flexible technique to easily calibrate a camera. It only requires the camera to observe a planar pattern shown at a few (at least two) different orientations. Either the camera or the planar pattern can be freely moved. The motion need not be known. Radial lens distortion is modeled. The proposed procedure consists of a closed-form solution, followed by a nonlinear refinement based on the maximum likelihood criterion. Both computer simulation and real data have been used to test the proposed technique and very good results have been obtained. Compared with classical techniques which use expensive equipment such as two or three orthogonal planes, the proposed technique is easy to use and flexible. It advances 3D computer vision one more step from laboratory environments to real world use.
13,200 citations
IBM1
TL;DR: In this paper, a two-stage technique for 3D camera calibration using TV cameras and lenses is described, aimed at efficient computation of camera external position and orientation relative to object reference coordinate system as well as the effective focal length, radial lens distortion, and image scanning parameters.
Abstract: A new technique for three-dimensional (3D) camera calibration for machine vision metrology using off-the-shelf TV cameras and lenses is described. The two-stage technique is aimed at efficient computation of camera external position and orientation relative to object reference coordinate system as well as the effective focal length, radial lens distortion, and image scanning parameters. The two-stage technique has advantage in terms of accuracy, speed, and versatility over existing state of the art. A critical review of the state of the art is given in the beginning. A theoretical framework is established, supported by comprehensive proof in five appendixes, and may pave the way for future research on 3D robotics vision. Test results using real data are described. Both accuracy and speed are reported. The experimental results are analyzed and compared with theoretical prediction. Recent effort indicates that with slight modification, the two-stage calibration can be done in real time.
5,940 citations
Book•
03 Jan 1992
TL;DR: A new technique for three-dimensional camera calibration for machine vision metrology using off-the-shelf TV cameras and lenses using two-stage technique has advantage in terms of accuracy, speed, and versatility over existing state of the art.
Abstract: A new technique for three-dimensional (3D) camera calibration for machine vision metrology using off-the-shelf TV cameras and lenses is described. The two-stage technique is aimed at efficient computation of camera external position and orientation relative to object reference coordinate system as well as the effective focal length, radial lens distortion, and image scanning parameters. The two-stage technique has advantage in terms of accuracy, speed, and versatility over existing state of the art. A critical review of the state of the art is given in the beginning. A theoretical framework is established, supported by comprehensive proof in five appendixes, and may pave the way for future research on 3D robotics vision. Test results using real data are described. Both accuracy and speed are reported. The experimental results are analyzed and compared with theoretical prediction. Recent effort indicates that with slight modification, the two-stage calibration can be done in real time.
5,816 citations
01 Jan 1978
4,100 citations
21 Sep 1999
TL;DR: A survey of the theory and methods of photogrammetric bundle adjustment can be found in this article, with a focus on general robust cost functions rather than restricting attention to traditional nonlinear least squares.
Abstract: This paper is a survey of the theory and methods of photogrammetric bundle adjustment, aimed at potential implementors in the computer vision community. Bundle adjustment is the problem of refining a visual reconstruction to produce jointly optimal structure and viewing parameter estimates. Topics covered include: the choice of cost function and robustness; numerical optimization including sparse Newton methods, linearly convergent approximations, updating and recursive methods; gauge (datum) invariance; and quality control. The theory is developed for general robust cost functions rather than restricting attention to traditional nonlinear least squares.
3,521 citations