Camera Calibration Model Research Articles

Camera calibration based on paraxial raytracing

Traditional camera calibration is based on the pinhole model, which is an approximation algorithm using untrue geometrical assumptions and giving a single lumped result for the multiple optical elements in a camera. To provide an alternative method of camera calibration, we extend the traditional 2×2 matrix-based paraxial raytracing method to 6×6 in order to trace paraxial rays by using the first-order Taylor series expansion of Snell’s laws. Then we establish the geometric relationship between images and objects. Compared with the Snell’s Law camera calibration model of our previous work, the paraxial model offers explicit analytical sensitivity analysis for the mathematical manipulation of problematical conditions. Compared with the existing pinhole model, the proposed method, in addition to five intrinsic and six extrinsic parameters, gives the position parameters of each optical element of the camera system.

Model-Free Uncalibrated Visual Servoing Using Recursive Least Squares

In this paper, a model free uncalibrated visual servoing algorithm based on recursive least squares is proposed and discussed in depth. No robot kinetics or dynamics, camera calibration or target model to be tracked would be ever needed. Based on the brief retrospection of RLS filter as well as its theoretical analysis, i.e. Wiener-Hopf condition, the core uncalibrated visual servoing algorithm based on recursive least squares is explored in detail. The experimental results of both static and moving targets applied on a Puma-560 6DOFs industrial robot simulation verifies its performances.

Introduction of New Associate Editors

The EiC and Associate EiC express our gratitude to David Forsyth, Brendan Frey, Venu Govindaraju, and Cordelia Schmid who are retiring as associate editors of TPAMI. While we will miss their dedication to the transactions, we hope that they will be enjoying a bit more free time. We are also pleased to announce that Professor Daniel Lopresti, Professor B.S. Manjunath, Professor Marc Pollefeys, and Professor Ramin Zabih have joined the editorial board. Professor Lopresti will oversee papers in document and handwriting analysis, biometrics, approximate string matching algorithms, and performance evaluation. Professor Manjunath will be considering papers in feature extraction, segmentation, image/video retrieval, and image registration. Professor Pollefeys will be responsible for submissions in structure from motion, stereo, multiple view geometry and camera calibration, 3D and appearance modeling, shape-from-X techniques, and novel sensors. Professor Zabih will handle papers on stereo and medical imaging as well as energy minimization and graph algorithms. We look forward to working with them. Their brief biographies appear herein.

Camera calibration with coplanar calibration board near parallel to the imaging plane

This paper presents a novel approach capable of estimating camera parameters under the condition that the calibration board is near parallel (or parallel) to the imaging plane. A camera calibration model for the near parallel condition is suggested. In the first step, based on the modified radial alignment constraint, the yaw angle and the X and Y translation components are analytically computed. In the second step, the closed-form solutions to the remaining parameters are provided by combining Gauss lens model with camera model, and they are refined by a nonlinear minimization procedure. Simulations and experiments are performed to verify the proposed camera calibration algorithm, and the precision of the automatic camera calibration scheme is also evaluated.

Introduction of New Associate Editors

The EiC and Associate EiC express our gratitude to David Forsyth, Brendan Frey, Venu Govindaraju, and Cordelia Schmid who are retiring as associate editors of TPAMI. While we will miss their dedication to the transactions, we hope that they will be enjoying a bit more free time. We are also pleased to announce that Professor Daniel Lopresti, Professor B.S. Manjunath, Professor Marc Pollefeys, and Professor Ramin Zabih have joined the editorial board. Professor Lopresti will oversee papers in document and handwriting analysis, biometrics, approximate string matching algorithms, and performance evaluation. Professor Manjunath will be considering papers in feature extraction, segmentation, image/video retrieval, and image registration. Professor Pollefeys will be responsible for submissions in structure from motion, stereo, multiple view geometry and camera calibration, 3D and appearance modeling, shape-from-X techniques, and novel sensors. Professor Zabih will handle papers on stereo and medical imaging as well as energy minimization and graph algorithms. We look forward to working with them. Their brief biographies appear herein.

Using geometric constraints through parallelepipeds for calibration and 3D modeling

This paper concerns the incorporation of geometric information in camera calibration and 3D modeling. Using geometric constraints enables more stable results and allows us to perform tasks with fewer images. Our approach is motivated and developed within a framework of semi-automatic 3D modeling, where the user defines geometric primitives and constraints between them. It is based on the observation that constraints, such as coplanarity, parallelism, or orthogonality, are often embedded intuitively in parallelepipeds. Moreover, parallelepipeds are easy to delineate by a user and are well adapted to model the main structure of, e.g., architectural scenes. In this paper, first a duality that exists between the shape parameters of a parallelepiped and the intrinsic parameters of a camera is described. Then, a factorization-based algorithm exploiting this relation is developed. Using images of parallelepipeds, it allows us to simultaneously calibrate cameras, recover shapes of parallelepipeds, and estimate the relative pose of all entities. Besides geometric constraints expressed via parallelepipeds, our approach simultaneously takes into account the usual self-calibration constraints on cameras. The proposed algorithm is completed by a study of the singular cases of the calibration method. A complete method for the reconstruction of scene primitives that are not modeled by parallelepipeds is also briefly described. The proposed methods are validated by various experiments with real and simulated data, for single-view as well as multiview cases.

Introduction of new Associate Editor

The EiC and Associate EiC express our gratitude to David Forsyth, Brendan Frey, Venu Govindaraju, and Cordelia Schmid who are retiring as associate editors of TPAMI. While we will miss their dedication to the transactions, we hope that they will be enjoying a bit more free time. We are also pleased to announce that Professor Daniel Lopresti, Professor B.S. Manjunath, Professor Marc Pollefeys, and Professor Ramin Zabih have joined the editorial board. Professor Lopresti will oversee papers in document and handwriting analysis, biometrics, approximate string matching algorithms, and performance evaluation. Professor Manjunath will be considering papers in feature extraction, segmentation, image/video retrieval, and image registration. Professor Pollefeys will be responsible for submissions in structure from motion, stereo, multiple view geometry and camera calibration, 3D and appearance modeling, shape-from-X techniques, and novel sensors. Professor Zabih will handle papers on stereo and medical imaging as well as energy minimization and graph algorithms. We look forward to working with them. Their brief biographies appear herein.

The Development of Camera Calibration Methods and Models

Correction for image distortion in cameras has been an important topic for as long as users have wanted to faithfully reproduce or use observed information. Initially the main application was mapping. While this task continues today, other applications also require precise calibration of cameras, such as close range three dimensional measurement and many two dimensional measurement tasks. In the past, the cameras used were few in number and highly expensive whereas today a typical large industrial company will have many inexpensive cameras being used for highly important measurement tasks. Cameras are used more today than they ever were but the golden age of camera calibration for aerial mapping is now well in the past. This paper considers some of the key developments and attempts to put them into perspective. In particular the driving forces behind each improvement have been highlighted.

Displacement and strain measurement with automated grid methods

An image-processing-based automated grid method is investigated to determine the method's displacement and strain accuracy limits, and how these limits are influenced by the choice of camera-calibration models. A CCD camera and a PC-based frame grabber are used to record grid spot motion, then ordering and centroiding are used to identify each spot and calculate their individual displacements. The displacements are fitted with a moving biquadratic surface, and the strains are obtained by analytical differentiation of that surface. Camera-calibration models which are considered include various combinations of image-perspective transformation, image stretching, and elliptical-lens distortion. The strain and displacement accuracy are explored through rigid-body motion and uniaxial tension tests. In the process, sensitivity to in-plane and out-of-plane rigid-body translation, and extreme sensitivity to in-plane rigid-body rotation (for non-synchronized frame grabbers) are confirmed. It is found that under the best conditions the displacement accuracy is 015 pixels and that the strain accuracy is 120 microstrain. Finally, the automated grid method is used to investigate the strains developed in an aluminum perforated strip subjected to uniaxial tension.