806 resultados para Lens distortion


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This paper discusses practical issues related to the use of the division model for lens distortion in multi-view geometry computation. A data normalisation strategy is presented, which has been absent from previous discussions on the topic. The convergence properties of the Rectangular Quadric Eigenvalue Problem solution for computing division model distortion are examined. It is shown that the existing method can require more than 1000 iterations when dealing with severe distortion. A method is presented for accelerating convergence to less than 10 iterations for any amount of distortion. The new method is shown to produce equivalent or better results than the existing method with up to two orders of magnitude reduction in iterations. Through detailed simulation it is found that the number of data points used to compute geometry and lens distortion has a strong influence on convergence speed and solution accuracy. It is recommended that more than the minimal number of data points be used when computing geometry using a robust estimator such as RANSAC. Adding two to four extra samples improves the convergence rate and accuracy sufficiently to compensate for the increased number of samples required by the RANSAC process.

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Accurate and efficient thermal-infrared (IR) camera calibration is important for advancing computer vision research within the thermal modality. This paper presents an approach for geometrically calibrating individual and multiple cameras in both the thermal and visible modalities. The proposed technique can be used to correct for lens distortion and to simultaneously reference both visible and thermal-IR cameras to a single coordinate frame. The most popular existing approach for the geometric calibration of thermal cameras uses a printed chessboard heated by a flood lamp and is comparatively inaccurate and difficult to execute. Additionally, software toolkits provided for calibration either are unsuitable for this task or require substantial manual intervention. A new geometric mask with high thermal contrast and not requiring a flood lamp is presented as an alternative calibration pattern. Calibration points on the pattern are then accurately located using a clustering-based algorithm which utilizes the maximally stable extremal region detector. This algorithm is integrated into an automatic end-to-end system for calibrating single or multiple cameras. The evaluation shows that using the proposed mask achieves a mean reprojection error up to 78% lower than that using a heated chessboard. The effectiveness of the approach is further demonstrated by using it to calibrate two multiple-camera multiple-modality setups. Source code and binaries for the developed software are provided on the project Web site.

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This paper presents an approach for the automatic calibration of low-cost cameras which are assumed to be restricted in their freedom of movement to either pan or tilt movements. Camera parameters, including focal length, principal point, lens distortion parameter and the angle and axis of rotation, can be recovered from a minimum set of two images of the camera, provided that the axis of rotation between the two images goes through the camera’s optical center and is parallel to either the vertical (panning) or horizontal (tilting) axis of the image. Previous methods for auto-calibration of cameras based on pure rotations fail to work in these two degenerate cases. In addition, our approach includes a modified RANdom SAmple Consensus (RANSAC) algorithm, as well as improved integration of the radial distortion coefficient in the computation of inter-image homographies. We show that these modifications are able to increase the overall efficiency, reliability and accuracy of the homography computation and calibration procedure using both synthetic and real image sequences

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Distributed Wireless Smart Camera (DWSC) network is a special type of Wireless Sensor Network (WSN) that processes captured images in a distributed manner. While image processing on DWSCs sees a great potential for growth, with its applications possessing a vast practical application domain such as security surveillance and health care, it suffers from tremendous constraints. In addition to the limitations of conventional WSNs, image processing on DWSCs requires more computational power, bandwidth and energy that presents significant challenges for large scale deployments. This dissertation has developed a number of algorithms that are highly scalable, portable, energy efficient and performance efficient, with considerations of practical constraints imposed by the hardware and the nature of WSN. More specifically, these algorithms tackle the problems of multi-object tracking and localisation in distributed wireless smart camera net- works and optimal camera configuration determination. Addressing the first problem of multi-object tracking and localisation requires solving a large array of sub-problems. The sub-problems that are discussed in this dissertation are calibration of internal parameters, multi-camera calibration for localisation and object handover for tracking. These topics have been covered extensively in computer vision literatures, however new algorithms must be invented to accommodate the various constraints introduced and required by the DWSC platform. A technique has been developed for the automatic calibration of low-cost cameras which are assumed to be restricted in their freedom of movement to either pan or tilt movements. Camera internal parameters, including focal length, principal point, lens distortion parameter and the angle and axis of rotation, can be recovered from a minimum set of two images of the camera, provided that the axis of rotation between the two images goes through the camera's optical centre and is parallel to either the vertical (panning) or horizontal (tilting) axis of the image. For object localisation, a novel approach has been developed for the calibration of a network of non-overlapping DWSCs in terms of their ground plane homographies, which can then be used for localising objects. In the proposed approach, a robot travels through the camera network while updating its position in a global coordinate frame, which it broadcasts to the cameras. The cameras use this, along with the image plane location of the robot, to compute a mapping from their image planes to the global coordinate frame. This is combined with an occupancy map generated by the robot during the mapping process to localised objects moving within the network. In addition, to deal with the problem of object handover between DWSCs of non-overlapping fields of view, a highly-scalable, distributed protocol has been designed. Cameras that follow the proposed protocol transmit object descriptions to a selected set of neighbours that are determined using a predictive forwarding strategy. The received descriptions are then matched at the subsequent camera on the object's path using a probability maximisation process with locally generated descriptions. The second problem of camera placement emerges naturally when these pervasive devices are put into real use. The locations, orientations, lens types etc. of the cameras must be chosen in a way that the utility of the network is maximised (e.g. maximum coverage) while user requirements are met. To deal with this, a statistical formulation of the problem of determining optimal camera configurations has been introduced and a Trans-Dimensional Simulated Annealing (TDSA) algorithm has been proposed to effectively solve the problem.

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A methodology for determining spacecraft attitude and autonomously calibrating star camera, both independent of each other, is presented in this paper. Unlike most of the attitude determination algorithms where attitude of the satellite depend on the camera calibrating parameters (like principal point offset, focal length etc.), the proposed method has the advantage of computing spacecraft attitude independently of camera calibrating parameters except lens distortion. In the proposed method both attitude estimation and star camera calibration is done together independent of each other by directly utilizing the star coordinate in image plane and corresponding star vector in inertial coordinate frame. Satellite attitude, camera principal point offset, focal length (in pixel), lens distortion coefficient are found by a simple two step method. In the first step, all parameters (except lens distortion) are estimated using a closed-form solution based on a distortion free camera model. In the second step lens distortion coefficient is estimated by linear least squares method using the solution of the first step to be used in the camera model that incorporates distortion. These steps are applied in an iterative manner to refine the estimated parameters. The whole procedure is faster enough for onboard implementation.

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结构光视觉传感器是视觉焊缝跟踪系统获得焊缝信息的重要组成部分,其测量误差与性能对焊缝跟踪系统的总体测量精度及可靠性有着直接影响。本文对应用于焊缝跟踪的结构光视觉传感器进行误差分析,包括传感器硬件系统结构误差、激光散斑噪声误差及镜头畸变误差等,并对不同结构方式下的视觉传感器建立了数学模型,具体分析了结构参数对其误差的影响,提出结构光视觉焊缝跟踪传感器优化设计方法,并依据仿真结果给出结构优化设计参数,最后通过实验验证了该优化设计方法的正确性。

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A robot mounted camera is useful in many machine vision tasks as it allows control over view direction and position. In this paper we report a technique for calibrating both the robot and the camera using only a single corresponding point. All existing head-eye calibration systems we have encountered rely on using pre-calibrated robots, pre- calibrated cameras, special calibration objects or combinations of these. Our method avoids using large scale non-linear optimizations by recovering the parameters in small dependent groups. This is done by performing a series of planned, but initially uncalibrated robot movements. Many of the kinematic parameters are obtained using only camera views in which the calibration feature is at, or near the image center, thus avoiding errors which could be introduced by lens distortion. The calibration is shown to be both stable and accurate. The robotic system we use consists of camera with pan-tilt capability mounted on a Cartesian robot, providing a total of 5 degrees of freedom.

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Image stitching is the process of joining several images to obtain a bigger view of a scene. It is used, for example, in tourism to transmit to the viewer the sensation of being in another place. I am presenting an inexpensive solution for automatic real time video and image stitching with two web cameras as the video/image sources. The proposed solution relies on the usage of several markers in the scene as reference points for the stitching algorithm. The implemented algorithm is divided in four main steps, the marker detection, camera pose determination (in reference to the markers), video/image size and 3d transformation, and image translation. Wii remote controllers are used to support several steps in the process. The built‐in IR camera provides clean marker detection, which facilitates the camera pose determination. The only restriction in the algorithm is that markers have to be in the field of view when capturing the scene. Several tests where made to evaluate the final algorithm. The algorithm is able to perform video stitching with a frame rate between 8 and 13 fps. The joining of the two videos/images is good with minor misalignments in objects at the same depth of the marker,misalignments in the background and foreground are bigger. The capture process is simple enough so anyone can perform a stitching with a very short explanation. Although real‐time video stitching can be achieved by this affordable approach, there are few shortcomings in current version. For example, contrast inconsistency along the stitching line could be reduced by applying a color correction algorithm to every source videos. In addition, the misalignments in stitched images due to camera lens distortion could be eased by optical correction algorithm. The work was developed in Apple’s Quartz Composer, a visual programming environment. A library of extended functions was developed using Xcode tools also from Apple.

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Considering the growing use of digital cameras in Photogrammetric projects, especially in aerial survey, this paper presents tests and analyses of bundle block adjustment with additional parameters, using different mathematical models, and blocks of images acquired by the SAAPI digital acquisition system. Three blocks of images were processed by the LPS (Leica Photogrammetry Suite) software, in which five groups of additional parameters (AP) can be used: Bauer, Jacobsen, Ebner, Brown and Lens distortion. These AP's models were employed in the bundle block adjustment, and the results were analyzed based on the accuracy of the checking points and on the changes in these additional parameters. The obtained results showed that the Lens Distortion model allowed the best results.

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A three-level satellite to ground monitoring scheme for conservation easement monitoring has been implemented in which high-resolution imagery serves as an intermediate step for inspecting high priority sites. A digital vertical aerial camera system was developed to fulfill the need for an economical source of imagery for this intermediate step. A method for attaching the camera system to small aircraft was designed, and the camera system was calibrated and tested. To ensure that the images obtained were of suitable quality for use in Level 2 inspections, rectified imagery was required to provide positional accuracy of 5 meters or less to be comparable to current commercially available high-resolution satellite imagery. Focal length calibration was performed to discover the infinity focal length at two lens settings (24mm and 35mm) with a precision of O.1mm. Known focal length is required for creation of navigation points representing locations to be photographed (waypoints). Photographing an object of known size at distances on a test range allowed estimates of focal lengths of 25.lmm and 35.4mm for the 24mm and 35mm lens settings, respectively. Constants required for distortion removal procedures were obtained using analytical plumb-line calibration procedures for both lens settings, with mild distortion at the 24mm setting and virtually no distortion found at the 35mm setting. The system was designed to operate in a series of stages: mission planning, mission execution, and post-mission processing. During mission planning, waypoints were created using custom tools in geographic information system (GIs) software. During mission execution, the camera is connected to a laptop computer with a global positioning system (GPS) receiver attached. Customized mobile GIs software accepts position information from the GPS receiver, provides information for navigation, and automatically triggers the camera upon reaching the desired location. Post-mission processing (rectification) of imagery for removal of lens distortion effects, correction of imagery for horizontal displacement due to terrain variations (relief displacement), and relating the images to ground coordinates were performed with no more than a second-order polynomial warping function. Accuracy testing was performed to verify the positional accuracy capabilities of the system in an ideal-case scenario as well as a real-world case. Using many welldistributed and highly accurate control points on flat terrain, the rectified images yielded median positional accuracy of 0.3 meters. Imagery captured over commercial forestland with varying terrain in eastern Maine, rectified to digital orthophoto quadrangles, yielded median positional accuracies of 2.3 meters with accuracies of 3.1 meters or better in 75 percent of measurements made. These accuracies were well within performance requirements. The images from the digital camera system are of high quality, displaying significant detail at common flying heights. At common flying heights the ground resolution of the camera system ranges between 0.07 meters and 0.67 meters per pixel, satisfying the requirement that imagery be of comparable resolution to current highresolution satellite imagery. Due to the high resolution of the imagery, the positional accuracy attainable, and the convenience with which it is operated, the digital aerial camera system developed is a potentially cost-effective solution for use in the intermediate step of a satellite to ground conservation easement monitoring scheme.

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Scientists planning to use underwater stereoscopic image technologies are often faced with numerous problems during the methodological implementations: commercial equipment is too expensive; the setup or calibration is too complex; or the imaging processing (i.e. measuring objects in the stereo-images) is too complicated to be performed without a time-consuming phase of training and evaluation. The present paper addresses some of these problems and describes a workflow for stereoscopic measurements for marine biologists. It also provides instructions on how to assemble an underwater stereo-photographic system with two digital consumer cameras and gives step-by-step guidelines for setting up the hardware. The second part details a software procedure to correct stereo-image pairs for lens distortions, which is especially important when using cameras with non-calibrated optical units. The final part presents a guide to the process of measuring the lengths (or distances) of objects in stereoscopic image pairs. To reveal the applicability and the restrictions of the described systems and to test the effects of different types of camera (a compact camera and an SLR type), experiments were performed to determine the precision and accuracy of two generic stereo-imaging units: a diver-operated system based on two Olympus Mju 1030SW compact cameras and a cable-connected observatory system based on two Canon 1100D SLR cameras. In the simplest setup without any correction for lens distortion, the low-budget Olympus Mju 1030SW system achieved mean accuracy errors (percentage deviation of a measurement from the object's real size) between 10.2 and -7.6% (overall mean value: -0.6%), depending on the size, orientation and distance of the measured object from the camera. With the single lens reflex (SLR) system, very similar values between 10.1% and -3.4% (overall mean value: -1.2%) were observed. Correction of the lens distortion significantly improved the mean accuracy errors of either system. Even more, system precision (spread of the accuracy) improved significantly in both systems. Neither the use of a wide-angle converter nor multiple reassembly of the system had a significant negative effect on the results. The study shows that underwater stereophotography, independent of the system, has a high potential for robust and non-destructive in situ sampling and can be used without prior specialist training.

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PURPOSE: To explore the experience of couples who continued pregnancy following a diagnosis of serious or lethal fetal anomaly. STUDY DESIGN: Thirty-one male and female participants were recruited from a high-risk maternal–fetal medicine clinic in Washington State. Data were collected using in-depth interviews during pregnancy and after the birth of their baby. Transcribed interviews were thematically analyzed through the phenomenological lens of Merleau-Ponty. FINDINGS: Participants described how time became reconfigured and reconstituted as they tried to compress a lifetime of love for their future child into a limited period. Participants’ concepts of time became distorted and were related to their perceptual lived experience rather than the schedule-filled,regimented, linear clock time that governed the health professionals. CONCLUSION: Living in distorted time may be a mechanism parents use to cope with overwhelming and disorienting feelings when their unborn baby is diagnosed with a fetal anomaly.

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When unmanned underwater vehicles (UUVs) perform missions near the ocean floor, optical sensors can be used to improve local navigation. Video mosaics allow to efficiently process the images acquired by the vehicle, and also to obtain position estimates. We discuss in this paper the role of lens distortions in this context, proving that degenerate mosaics have their origin not only in the selected motion model or in registration errors, but also in the cumulative effect of radial distortion residuals. Additionally, we present results on the accuracy of different feature-based approaches for self-correction of lens distortions that may guide the choice of appropriate techniques for correcting distortions

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The extent to which the surface parameters of Progressive Addition Lenses (PALs) affect successful patient tolerance was investigated. Several optico-physical evaluation techniques were employed, including a newly constructed surface reflection device which was shown to be of value for assessing semi-finished PAL blanks. Detailed physical analysis was undertaken using a computer-controlled focimeter and from these data, iso-cylindrical and mean spherical plots were produced for each PAL studied. Base curve power was shown to have little impact upon the distribution of PAL astigmatism. A power increase in reading addition primarily caused a lengthening and narrowing of the lens progression channel. Empirical measurements also indicated a marginal steepening of the progression power gradient with an increase in reading addition power. A sample of the PAL wearing population were studied using patient records and questionnaire analysis (90% were returned). This subjective analysis revealed the reading portion to be the most troublesome lens zone and showed that patients with high astigmatism (> 2.00D) adapt more readily to PALs than those with spherical or low cylindrical (2.00D) corrections. The psychophysical features of PALs were then investigated. Both grafting visual acuity (VA) and contrast sensitivity (CS) were shown to be reduced with an increase in eccentricity from the central umbilical line. Two sample populations (N= 20) of successful and unsuccessful PAL wearers were assessed for differences in their visual performance and their adaptation to optically induced distortion. The possibility of dispensing errors being the cause of poor patient tolerance amongst the unsuccessful wearer group was investigated and discounted. The contrast sensitivity of the successful group was significantly greater than that of the unsuccessful group. No differences in adaptation to or detection of curvature distortion were evinced between these presbyopic groups.