Camera Intrinsic Parameters Research Articles

Analyzing crack development pattern of masonry structure in seismic oscillation by digital photography

In this study, digital photography is used to monitor the instantaneous deformation of a masonry wall in seismic oscillation. In order to obtain higher measurement accuracy, the image matching-time baseline parallax method (IM-TBPM) is used to correct errors caused by the change of intrinsic and extrinsic parameters of digital cameras. Results show that the average errors of control point C5 are 0.79mm, 0.44mm and 0.96mm in X, Z and comprehensive direction, respectively. The average errors of control point C6 are 0.49mm, 0.44mm and 0.71mm in X, Z and comprehensive direction, respectively. These suggest that IM-TBPM can meet the accuracy requirements of instantaneous deformation monitoring. In seismic oscillation the middle to lower of the masonry wall develops cracks firstly. Then the shear failure occurs on the middle of masonry wall. This study provides technical basis for analyzing the crack development pattern of masonry structure in seismic oscillation and have significant implications for improved construction of masonry structures in earthquake prone areas.

Real-Time Android Application for Traffic Density Estimation

This paper deals with automatic traffic density estimation using new technologies that are cost-effective, quick to deploy, and easy to adapt. Therefore, a real-time video processing-based android application ( $app$ ) is developed. It can be used online by exploiting the smartphone’s camera placed at the roadside or offline and by using pre-recorded vehicles flow videos and an Android emulator. The system autonomously computes the vehicle flow density in real time and saves all the relevant information in the smartphone memory. The developed app is validated under real conditions in Sherbrooke and Montreal cities, by considering different meteorological conditions and varying intrinsic and extrinsic camera parameters. Obtained results allow being optimistic about the effectiveness and the applicability of the proposed app .

Técnica Flexible de Zhang para el cálculo de parámetros intrínsecos y extrínsecos en el ajuste de dietas en cultivos de Oreochromis Sp

<p>El cálculo de los parámetros intrínsecos y extrínsecos de cámaras digitales usadas en los cultivos de Tilapias, facilita el ajuste de dichas cámaras a las medidas biométricas reales que se esperan obtener del cultivo. Con estos cálculos se busca crear un modelo matemático que permita relacionar las medidas en pixeles del sensor óptico de las cámaras con las medidas biométricas de las tilapias. Para encontrar la talla de la tilapia roja por medio de reconocimiento de imágenes digitales se determinaron las características internas, geométricas y ópticas de la cámara (Parámetros intrínsecos) y la posición de referencia de la cámara, con respecto al acuario o estanque (parámetros extrínsecos). El propósito era hallar un modelo matemático que permitiera obtener la información biométrica de las tilapias a partir de las imágenes digitales obtenidas por la cámara. Para este caso, se aplicó el método de calibración de Zhang, utilizando imágenes de un plano con patrones de intensidad específicos, capturados por la cámara en diferentes posiciones y orientaciones. Con los parámetros encontrados se buscó el modelo matemático que relacionara las medidas reales biométricas de las tilapias con el análisis de las imágenes digitalizadas.</p>

Accurate calibration of a multi-camera system based on flat refractive geometry.

Multi-camera systems are widely applied in many fields, but the camera calibration is particularly important and difficult. In the application of a multi-camera system, it is very common for multiple cameras to be distributed on both sides of the measured object with overlapping field of view. In this paper, we present a novel calibration method for a multi-camera system based on flat refractive geometry. All cameras in the system can acquire calibration images of a transparent glass calibration board (TGCB) at the same time. The application of TGCB leads to a refractive phenomenon that can generate calibration error. The theory of flat refractive geometry is employed to eliminate the error. The proposed method combines the camera projection model with flat refractive geometry to determine the intrinsic and extrinsic camera parameters. The bundle adjustment method is employed to minimize the reprojection error and obtain optimized calibration results. The simulation is performed with zero-mean Gaussian noise of the standard deviation changes from 0 to 0.4 pixels, and the results show that the error of rotation angle is less than 5.6e-3 deg, and the error of translation is less than 4.6e-3 mm. The four-camera calibration results of real data show that the mean value and standard deviation of the reprojection error of our method are 4.3411e-05 and 0.4553 pixels, respectively. Both the simulative and real experiments show that the proposed method is accurate and feasible.

Three-line structured light measurement system and its application in ball diameter measurement

This paper proposes a three-dimensional measurement system of three-line structured light for ball diameter. In the system, firstly, the BP neural network is used to correct the distortion model of the camera. Zhang Zhenyou’s plane calibration method is adopted to get the camera's intrinsic and extrinsic parameters. Secondly, a sub-pixel extraction method for the center of the three-line structured light stripe is put forward to achieve sub-pixel accuracy, which is integrated by the adaptive median filtering method, threshold segmentation method, mean square gray gradient method and weighted gray center of gravity method. Finally, a three-line structured light three-dimensional measurement platform is developed, and the ball diameter measurement is carried out. It shows that the proposed method is valid, flexible and with high precision by experiment, and the three-line structured light three-dimensional measurement system can meet the requirements of high-precision and speed.

Planar self-calibration for stereo cameras with radial distortion.

In this paper, we present a robust technique of stereo calibration using homography constraints. Our method is novel as stereo calibration is performed by solving a polynomial equation system including two radial distortion parameters, using a minimal number of five image point correspondences. This enables us to calibrate from only a pair of stereo images of a planar scene, and to provide the exact algebraic solution to the stereo calibration problem. The minimal case solution is useful to reduce the computation time and increase the calibration robustness when using random sample consensus (RANSAC) from the correspondences of the stereo image pair. Further, a non-linear parameter optimization for the intrinsic and extrinsic parameters of stereo cameras is performed using the inliers, which are determined after RANSAC. In addition, our method can achieve more robust calibration results with multiple stereo image pairs by performing joint optimization. In contrast to the previous stereo calibration methods, our method works without requiring any special hardware and has no problems with one stereo image pair, even corrupted by severe radial distortions. Finally, by evaluating our method on both synthetic and real scene data, we demonstrate that our method is both efficient and accurate for stereo calibration.

Robust geometric, phase and colour structured light projection system calibration

This paper introduces a new comprehensive procedure for both geometric and colour calibration of structured light system. In order to perform both geometric and colour calibration procedure, a new calibration artifact is proposed. The intrinsic and extrinsic parameters of projector and camera are estimated by using an extended pinhole camera model with a tangential and radial distortion. Camera image plane coordinates are obtained by extracting features from images of a calibration artifact. Projector image plane coordinates are calculated on the basis of continuous phase maps obtained from a fringe pattern phase reconstruction procedure. In order to stereo calibrate camera-projector system, pairs of corresponding image plane points are calculated with subpixel accuracy. In addition, one of three pattern views is used in colour calibration. RGB values of a colour field pattern detected by camera and their reference values are compared. This comparison leads to derivation of a colour transformation matrix. The performance of the proposed method is tested by measuring plane, sphere and distance reference. Also 360 degrees complex object 3D model from a set of measurements is obtained. Residual mean errors for all tests performed are calculated.

Phase-locked optical metrology I: identification of intrinsic camera parameters from multiple grid views.

Camera-based optical metrology crucially relies on a proper identification of intrinsic (optical center position) and extrinsic (camera position) parameters of the used camera. A novel approach for processing phase data from multiple views of a target grid is presented, allowing these identifications within a pinhole camera model. First, the homography associated with the perspective distortion of each grid image is accurately identified using a phase-locking loop. Then, the affine transform for each view is determined, with the constraint of an identical set of intrinsic camera parameters. This requires slightly adjusting each homography. As there are highly redundant data, a criterion has to be chosen to optimize the result. The chosen criterion is the simultaneous minimization of the standard deviation between in-plane grid line displacements between the acquired grid images and the reconstructed ones. Experimental results demonstrate the efficiency of the method.

Fitting a cluster of line images under central catadioptric camera

Generally, due to the partial occlusion, it is very difficult to correctly estimate the central catadioptric line image from its visible part. Except for the necessary and sufficient conditions that must be satisfied by a set of paracatadioptric line images, we find that if the antipodal points of image points on the visible arc are known, the fitting accuracy can be improved greatly. In this paper, we propose a new method for fitting line images, which can be applied to all central catadioptric projection. Firstly, a new relationship between a pair of antipodal image points and the camera principal point is derived. Next, using this relationship, a new method is proposed to estimate the line images. These estimated line images are used to calibrate camera intrinsic parameters to evaluate the performance of our fitting method. Experimental results on both simulated and real data have demonstrated the effectiveness of our method.

Single Frame Resection of Compact Digital Cameras for UAV Imagery

Recently, UAVs (Unmanned Aerial Vehicles) gain a wider acceptance from many disciplines. One major application is for monitoring and mapping. Flying beyond eye sight autonomously and collecting data over large areas are their obvious advantages. To support a large scale urban city mapping, we have developed a UAV system which can carry a compact digital camera as well as a navigational grade of a Global Positioning System (GPS) board mounted on the vehicle. Unfortunately, such a navigational system fails to provide sufficient accuracy required to process images become a large scale map. Ubiquitous digital compact cameras, despite their low cost benefits, are widely known to suffer instabilities in their internal lenses and electronics imaging system. Hence these cameras are less suitable for mapping related purposes. However, this paper presents a photogrammetric technique to precisely determine intrinsic and extrinsic camera parameters of photographed images provided that sufficient numbers of surveyed control points are available. A rigorous Mathematical model is derived to compute each image position with respect to the imaging coordinate system as well as a location of the principal point of an image sensor and the focal length of the camera. An iterative Gaussian-Newton least squares adjustment method is utilized to compute those parameters. Finally, surveyed data are processed and elaborated to justify the mathematical models.

Planar content selection in images and videos using frontalness

This paper addresses the problem of selecting instances of a planar object in a video or from a set of images based on an evaluation of its “frontalness”. We introduce the idea of “evaluating the frontalness” by computing how close the object’s surface normal aligns with the optical axis of a camera. Unlike previous planar object pose estimation methods, our method does not require the true frontal image as a reference. The intuition is that a true frontal image can produce other non-frontal images by perspective projection, while the non-frontal images have limited ability to produce other non-frontal images. We show that this intuition of comparing ‘frontal’ and ‘non-frontal’ can be extended to comparing ‘more frontal’ and ‘less frontal’ images. Based on this observation, our method estimates the relative frontalness of an image by exploiting the objective space error. We also propose the use of K-invariant space to evaluate the frontalness even when the camera intrinsic parameters are unknown (e.g., images/videos from the web). Our method outperforms the homography decomposition-based method and does not require reference images. A qualitative evaluation is also carried out to show that our method can be applied in selecting the most frontal characters from a set of images captured in various viewpoints.

An Optimized Adaptive Camera Calibration Algorithm

Camera calibration is a basic problem in computer vision. An optimized adaptive camera calibration method is proposed in this paper, which can efficiently and precisely calibrate cameras. Our calibration method is easy-to-use by using only one calibration board. In our method, we do lens distortion rectification and camera intrinsic and extrinsic parameters estimation separately, which increase the precision of lens distortion rectification. Meanwhile, dimensions are reduced in nonlinear optimization of camera parameters. By means of alternatively optimize camera’s intrinsic and extrinsic parameter in nonlinear optimization, our method reduces the calibration error by at most 63.14% compared to Zhang’s method [1].

A new vision measurement method based on active object gazing

A new vision measurement system is developed with two cameras. One is fixed in pose to serve as a monitor camera. It finds and tracks objects in image space. The other is actively rotated to track the object in Cartesian space, working as an active object-gazing camera. The intrinsic parameters of the monitor camera are calibrated. The view angle corresponding to the object is calculated from the object’s image coordinates and the camera’s intrinsic parameters. The rotation angle of the object-gazing camera is measured with an encoder. The object’s depth is computed with the rotation angle and the view angle. Then the object’s three-dimensional position is obtained with its depth and normalized imaging coordinates. The error analysis is provided to assess the measurement accuracy. The experimental results verify the effectiveness of the proposed vision system and measurement method.

Multicamera rig calibration by double‐sided thick checkerboard

A multi‐camera rig calibration algorithm based on a double sided planar target is proposed. Due to their inherently simple realisation, low cost and accuracy, planar calibration targets came out as one of the most largely adopted calibration tools both for intrinsic and extrinsic camera parameters. However, concerning the estimation of extrinsic parameters, one of the major drawbacks of these targets is their requirement for distinct target visibility from both cameras. This prevents many configurations from being adopted where, e.g. two cameras are facing each other. An inexpensive solution could be based on printing/pasting a planar pattern on both target sides, however, the relative misalignment between the patterns on the two sides and the target thickness could be unknown. The authors propose a solution where double‐sided target displacement error is estimated together with the extrinsic parameters allowing the reuse of all the available planar calibration tools in less constrained configurations. To assess their approach the authors tested the system in two scenarios, one using two professional 4K cameras and one using two smartphones.

A General Solution for Iso-Disparity Layers and Correspondence Field Model for Stereo Systems

Estimation of localization error and selection of system parameters are the key factors in evaluation of visual 3-D systems. Iso-disparity layers and correspondence field are recently introduced to present a graphical model for space sampling in general 3-D systems. The correspondence field describes the spatial topology of the intersecting rays of cameras, arranged in a number of layers or surfaces with same disparity values, referred as iso-disparity layers. This paper develops a mathematical framework to investigate the geometrical variations of these layers with respect to camera intrinsic and extrinsic parameters. It will be demonstrated that the layers in their general form appear as a set of quadric surfaces, where the coefficients of these quadrics depend on system parameters. The distance between the iso-disparity layers due to the quantization process is suggested as a measure of uncertainty and can be considered as a criterion for appropriate selection of parameters, such as focal length, position, and orientation of cameras for the system to achieve desirable precision. Here, we use an analytical solution to calculate the orthogonal distance between the two successive iso-disparity layers. These distances are representatives of depth uncertainty. Finally, we have simulated our model and the results verify that the total average error is less than 2%.

HIERARCHICAL STRUCTURE FROM MOTION COMBINING GLOBAL IMAGE ORIENTATION AND STRUCTURELESS BUNDLE ADJUSTMENT

Abstract. Global image orientation techniques aim at estimating camera rotations and positions for a whole set of images simultaneously. One of the main arguments for these procedures is an improved robustness against drifting of camera stations in comparison to more classical sequential approaches. Usually, the process consists of computation of absolute rotations and, in a second step, absolute positions for the cameras. Either the first or both steps rely on the network of transformations arising from relative orientations between cameras. Therefore, the quality of the obtained absolute results is influenced by tensions in the network. These may e.g. be induced by insufficient knowledge of the intrinsic camera parameters. Another reason can be found in local weaknesses of image connectivity. We apply a hierarchical approach with intermediate bundle adjustment to reduce these effects. We adopt efficient global techniques which register image triplets based on fixed absolute camera rotations and scaled relative camera translations but do not involve scene structure elements in the fusion step. Our variant employs submodels of arbitrary size, orientation and scale, by computing relative rotations and scales between - and subsequently absolute rotations and scales for - submodels and is applied hierarchically. Furthermore we substitute classical bundle adjustment by a structureless approach based on epipolar geometry and augmented with a scale consistency constraint.

Camera self-calibration from projection silhouettes of an object in double planar mirrors.

In double planar mirror omnidirectional imaging systems, camera calibration is a crucial part of the 3D reconstruction process. Based on analysis of the imaging geometric features of double planar mirrors, three types of algorithms for the camera intrinsic parameters are presented by computing the imaged circular points and orthogonal vanishing points. The camera intrinsic parameters can be obtained by the constraints on the imaged circular points and the orthogonal vanishing points to the image of the absolute conic. Simulation, real data, and 3D reconstruction experiments are presented to show the feasibility and validity of the proposed methods.

Effective self-calibration for camera parameters and hand-eye geometry based on two feature points motions

A novel and effective self-calibration approach for robot vision is presented, which can effectively estimate both the camera intrinsic parameters and the hand-eye transformation at the same time. The proposed calibration procedure is based on two arbitrary feature points of the environment, and three pure translational motions and two rotational motions of robot endeffector are needed. New linear solution equations are deduced, and the calibration parameters are finally solved accurately and effectively. The proposed algorithm has been verified by simulated data with different noise and disturbance. Because of the need of fewer feature points and robot motions, the proposed method greatly improves the efficiency and practicality of the calibration procedure.

Adaptive Vision-Based Leader–Follower Formation Control of Mobile Robots

This paper focuses on the problem of vision-based leader–follower formation control of mobile robots. The proposed adaptive controller only requires the image information from an uncalibrated perspective camera mounted at any position and orientation (attitude) on the follower robot. Furthermore, the approach does not depend on the relative position measurement and communication between the leader and follower. First, a new real-time observer is developed to estimate the unknown intrinsic and extrinsic camera parameters as well as the unknown coefficients of the plane where the feature point moves relative to the camera frame. Second, the Lyapunov method is employed to prove the stability of the closed-loop system, where it is shown that convergence of the image error is guaranteed. Finally, the performance of the approach is demonstrated through physical experiments and experimental results.

Robust extrinsic calibration from pedestrians

Calibration from pedestrians in the single-camera setup is studied in this paper. Previous relevant methods are mainly designed in simple scenes with a single pedestrian. The objective of this paper is to improve the calibration performance in complex scenes with crowds. Different methods in previous work are evaluated and compared. Under the assumption of known camera intrinsic parameters, a novel metric for vanishing line estimation is proposed, and WCS reference is incorporated into the calibration method. Experiments are conducted on the PETS′09 dataset with crowds and the Town Center dataset in real world. The experimental results prove that the proposed metric outperforms previous metrics in the calibration, and the refinements of WCS reference can further improve the calibration accuracy.