3,042 research outputs found

    Infrastructure-based Multi-Camera Calibration using Radial Projections

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    Multi-camera systems are an important sensor platform for intelligent systems such as self-driving cars. Pattern-based calibration techniques can be used to calibrate the intrinsics of the cameras individually. However, extrinsic calibration of systems with little to no visual overlap between the cameras is a challenge. Given the camera intrinsics, infrastucture-based calibration techniques are able to estimate the extrinsics using 3D maps pre-built via SLAM or Structure-from-Motion. In this paper, we propose to fully calibrate a multi-camera system from scratch using an infrastructure-based approach. Assuming that the distortion is mainly radial, we introduce a two-stage approach. We first estimate the camera-rig extrinsics up to a single unknown translation component per camera. Next, we solve for both the intrinsic parameters and the missing translation components. Extensive experiments on multiple indoor and outdoor scenes with multiple multi-camera systems show that our calibration method achieves high accuracy and robustness. In particular, our approach is more robust than the naive approach of first estimating intrinsic parameters and pose per camera before refining the extrinsic parameters of the system. The implementation is available at https://github.com/youkely/InfrasCal.Comment: ECCV 202

    Development of a stereovision-based technique to measure the spread patterns of granular fertilizer spreaders

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    Centrifugal fertilizer spreaders are by far the most commonly used granular fertilizer spreader type in Europe. Their spread pattern however is error-prone, potentially leading to an undesired distribution of particles in the field and losses out of the field, which is often caused by poor calibration of the spreader for the specific fertilizer used. Due to the large environmental impact of fertilizer use, it is important to optimize the spreading process and minimize these errors. Spreader calibrations can be performed by using collection trays to determine the (field) spread pattern, but this is very time-consuming and expensive for the farmer and hence not common practice. Therefore, we developed an innovative multi-camera system to predict the spread pattern in a fast and accurate way, independent of the spreader configuration. Using high-speed stereovision, ejection parameters of particles leaving the spreader vanes were determined relative to a coordinate system associated with the spreader. The landing positions and subsequent spread patterns were determined using a ballistic model incorporating the effect of tractor motion and wind. Experiments were conducted with a commercial spreader and showed a high repeatability. The results were transformed to one spatial dimension to enable comparison with transverse spread patterns determined in the field and showed similar results

    The Geometry and Usage of the Supplementary Fisheye Lenses in Smartphones

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    Nowadays, mobile phones are more than a device that can only satisfy the communication need between people. Since fisheye lenses integrated with mobile phones are lightweight and easy to use, they are advantageous. In addition to this advantage, it is experimented whether fisheye lens and mobile phone combination can be used in a photogrammetric way, and if so, what will be the result. Fisheye lens equipment used with mobile phones was tested in this study. For this, standard calibration of ‘Olloclip 3 in one’ fisheye lens used with iPhone 4S mobile phone and ‘Nikon FC‐E9’ fisheye lens used with Nikon Coolpix8700 are compared based on equidistant model. This experimental study shows that Olloclip 3 in one fisheye lens developed for mobile phones has at least the similar characteristics with classic fisheye lenses. The dimensions of fisheye lenses used with smart phones are getting smaller and the prices are reducing. Moreover, as verified in this study, the accuracy of fisheye lenses used in smartphones is better than conventional fisheye lenses. The use of smartphones with fisheye lenses will give the possibility of practical applications to ordinary users in the near future

    A Multi-Projector Calibration Method for Virtual Reality Simulators with Analytically Defined Screens

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    The geometric calibration of projectors is a demanding task, particularly for the industry of virtual reality simulators. Different methods have been developed during the last decades to retrieve the intrinsic and extrinsic parameters of projectors, most of them being based on planar homographies and some requiring an extended calibration process. The aim of our research work is to design a fast and user-friendly method to provide multi-projector calibration on analytically defined screens, where a sample is shown for a virtual reality Formula 1 simulator that has a cylindrical screen. The proposed method results from the combination of surveying, photogrammetry and image processing approaches, and has been designed by considering the spatial restrictions of virtual reality simulators. The method has been validated from a mathematical point of view, and the complete system which is currently installed in a shopping mall in Spain has been tested by different users

    Quantitative evaluation of overlaying discrepancies in mobile augmented reality applications for AEC/FM

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    Augmented Reality (AR) is a trending technology that provides a live view of the real and physical environment augmented by virtual elements, enhancing the information of the scene with digital information (sound, video, graphics, text or geo-location). Its application to architecture, engineering and construction, and facility management (AEC/FM) is straightforward and can be very useful to improve the on-site work at different stages of the projects. However, one of the most important limitations of Mobile Augmented Reality (MAR) is the lack of accuracy when the screen overlays the virtual models on the real images captured by the camera. The main reasons are errors related to tracking (positioning and orientation of the mobile device) and image capture and processing (projection and distortion issues). This paper shows a new methodology to mathematically perform a quantitative evaluation, in world coordinates, of those overlaying discrepancies on the screen, obtaining the real-scale distances from any real point to the sightlines of its virtual projections for any AR application. Additionally, a new utility for filtering built-in sensor signals in mobile devices is presented: the Drift-Vibration-Threshold function (DVT), a straightforward tool to filter the drift suffered by most sensor-based tracking systems

    Planar PØP: feature-less pose estimation with applications in UAV localization

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    © 20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.We present a featureless pose estimation method that, in contrast to current Perspective-n-Point (PnP) approaches, it does not require n point correspondences to obtain the camera pose, allowing for pose estimation from natural shapes that do not necessarily have distinguished features like corners or intersecting edges. Instead of using n correspondences (e.g. extracted with a feature detector) we will use the raw polygonal representation of the observed shape and directly estimate the pose in the pose-space of the camera. This method compared with a general PnP method, does not require n point correspondences neither a priori knowledge of the object model (except the scale), which is registered with a picture taken from a known robot pose. Moreover, we achieve higher precision because all the information of the shape contour is used to minimize the area between the projected and the observed shape contours. To emphasize the non-use of n point correspondences between the projected template and observed contour shape, we call the method Planar PØP. The method is shown both in simulation and in a real application consisting on a UAV localization where comparisons with a precise ground-truth are provided.Peer ReviewedPostprint (author's final draft

    Generation Of An Accurate, Metric Spatial Database Of A Large Multi Storied Building

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    This thesis presents the development of a novel method to generate an accurate, metric spatial database of a large multi storied building during construction. The algorithm uses the 3D CAD model of the building and the video of the structure captured by an Unmanned Aircraft System (UAS). The spatial database is then used to perform several inspection procedures such as, metric data analysis, spatial query for images, visualization through 3D textured model. The video is processed using a simultaneous localization and mapping (SLAM) system. SLAM generates a sparse 3D map of the environment. Our algorithm registers the 3D map with the 3D CAD model to generate the accurate metric spatial database. The user can click on the desired part of the CAD model for inspection and the image of that part will be shown by using the spatial indexing between the CAD model and the spatially distributed images. The image returned by the spatial query can be used to extract metric information. The spatial database is also used to generate a 3D textured model which provides a visual as-built documentation. The metric data calculation and textured model reconstruction methods have been compared to the state of the art Pix4D software (Latest Release (Version 3.1)). The proposed method has a mean squared error (MSE) of 31.9 cm2 and standard deviation of 4.28 cm where Pix4D had a higher MSE of 45.6 cm2 and standard deviation of 4.91 cm. Using statistical t-test and ANOVA tests we have shown that we are statistically 99% confident that the proposed algorithm has performed better than Pix4D

    The Dark Energy Survey

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    We describe the Dark Energy Survey (DES), a proposed optical-near infrared survey of 5000 sq. deg of the South Galactic Cap to ~24th magnitude in SDSS griz, that would use a new 3 sq. deg CCD camera to be mounted on the Blanco 4-m telescope at Cerro Telolo Inter-American Observatory (CTIO). The survey data will allow us to measure the dark energy and dark matter densities and the dark energy equation of state through four independent methods: galaxy clusters, weak gravitational lensing tomography, galaxy angular clustering, and supernova distances. These methods are doubly complementary: they constrain different combinations of cosmological model parameters and are subject to different systematic errors. By deriving the four sets of measurements from the same data set with a common analysis framework, we will obtain important cross checks of the systematic errors and thereby make a substantial and robust advance in the precision of dark energy measurements.Comment: White Paper submitted to the Dark Energy Task Force, 42 page
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