External Orientation Parameters Research Articles

THE UTILIZATION OF SYNTHETIC AND SEMISYNTHETIC POINT CLOUDS AND IMAGES FOR TESTING NOVEL APPROACHES FOR CORRECTING LIDAR DATA

Abstract. The paper presents the application of lidar data and photo datasets, external orientation parameters (EOPs), ground control points (GCPs), and check points for testing new methods of geometric lidar data correction. These datasets are utilized to validate novel approaches such as altimetric deformation methods based on stereo models or lidargrammetric methods that utilize image matching and specialized lidar data formats. The paper presents specific use cases of these data as examples of two tested processes. After describing these processes, the methods of synthetic and semisynthetic data simulation are presented. The simulation is directed and subordinated to the aspects of the new method being tested. The data must be used for testing starting from basic functionality up to specific and untypical cases of new method application. By presenting specific cases of the application of synthetic and semisynthetic data, the paper introduces the general idea of benchmarking based on synthetic and semisynthetic data as another means of validating new methods. These artificially generated datasets provide a controlled environment for evaluating the effectiveness of new methods to be investigated.

Adoption of Digital Aerial Photogrammetry in Forest Planning: A Case Study of Canavese Forestry Consortium, NW Italy with Technical and Economic Issues

The forestry sector has been significantly affected by the recent advances in geomatics. Photogrammetric aerial acquisitions provide full coverage of forests, making possible a wall-to-wall mapping of the main forestry key variables, such as tree height and tree density, needed for forest planning and management purposes. This work summarizes the role that digital aerial photogrammetry (DAP) is expected to have in the forest planning context and analyzes the main products from DAP that are significantly required. According to their technical features, some strategies are proposed to program acquisitions in order to consciously set operational parameters needed for obtaining accuracy of measures compliant with forest planning requirements. Admitting that, in most cases, forest planners externalize DAP acquisitions to flying companies, the authors propose simple strategies for making an ex-post evaluation of flight conditions through a conscious processing of the external orientation parameters of images resulting after the bundle adjustment. Theoretical aspects are exemplified with reference to a practical case study relying on an aerial acquisition that, in 2019, the Canavese Forestry Consortium (NW Italy) made to support the ongoing redaction of its new forest plans. Finally, some economic concerns are presented to demonstrate the capability of this technique to absorb the most of costs associated with ground surveys, especially when large areas have to be investigated. In particular, about 66% of cost savings were found when comparing DAP-based forest mapping to traditional forest inventory strategies.

OVERVIEW OF OPEN SOURCE SOFTWARE FOR CLOSE RANGE PHOTOGRAMMETRY

Abstract. In the photogrammetric process of the 3D reconstruction of an object or a building, multi-image orientation is one of the most important tasks that often include simultaneous camera calibration. The accuracy of image orientation and camera calibration significantly affects the quality and accuracy of all subsequent photogrammetric processes, such as determining the spatial coordinates of individual points or 3D modeling. In the context of artificial vision, the full-field analysis procedure is used, which leads to the so-called Strcture from Motion (SfM), which includes the simultaneous determination of the camera's internal and external orientation parameters and the 3D model. The procedures were designed and developed by means of a photogrammetric system, but the greatest development and innovation of these procedures originated from the computer vision from the late 90s, together with the SfM method. The reconstructions on this method have been useful for visualization purposes and not for photogrammetry and mapping. Thanks to advances in computer technology and computer performance, a large number of images can be automatically oriented in a coordinate system arbitrarily defined by different algorithms, often available in open source software (VisualSFM, Bundler, PMVS2, CMVS, etc.) or in the form of Web services (Microsoft Photosynth, Autodesk 123D Catch, My3DScanner, etc.). However, it is important to obtain an assessment of the accuracy and reliability of these automated procedures. This paper presents the results obtained from the dome low close range photogrammetric surveys and processed with some open source software using the Structure from Motion approach: VisualSfM, OpenDroneMap (ODM) and Regard3D. Photogrammetric surveys have also been processed with the Photoscan commercial software by Agisoft.For the photogrammetric survey we used the digital camera Canon EOS M3 (24.2 Megapixel, pixel size 3.72 mm). We also surveyed the dome with the Faro Focus 3D TLS. Only one scan was carried out, from ground level, at a resolution setting of ¼ with 3x quality, corresponding to a resolution of 7 mm / 10 m. Both TLS point cloud and Photoscan point cloud were used as a reference to validate the point clouds coming from VisualSFM, OpenDroneMap and Regards3D. The validation was done using the Cloud Compare open source software.

MAGO: A NEW APPROACH FOR ORTHOPHOTOS PRODUCTION BASED ON ADAPTIVE MESH RECONSTRUCTION

Abstract. Orthophotos are one of the most common and typical products of a photogrammetric post-processing and, since the diffusion of specific software, their generation and usage have become even more widespread. In spite of it, some issues remain on the accuracy of orthophoto reconstruction, which is often downgraded by the introduction of meshes and Digital Surface Models to be used as surfaces representing the object. The use of a more accurate and reliable input, such as a point cloud, makes these approximations avoidable. For this reason, a new approach, termed MAGO (Adaptive Mesh for Orthophoto Reconstruction), is here delineated and proposed. The input data of the procedure are the user-defined orthophoto plane, the image and its internal and external orientation parameters, and a point cloud representing the object. Each pixel of the image is projected on the orthophoto plane at its original resolution via an iterative process, which builds an adaptive mesh, defined by means of the three best fitting points, where the collinearity rays and the point cloud intersect. After an overview on the method and its innovative features, an example on a test case is reported, together with a comparison between MAGO’s and another photogrammetric software results.

ASSESSING THE RELIABILITY AND THE ACCURACY OF ATTITUDE EXTRACTED FROM VISUAL ODOMETRY FOR LIDAR DATA GEOREFERENCING

Abstract. Airborne LiDAR systems require the use of Direct Georeferencing (DG) in order to compute the coordinates of the surveyed point in the mapping frame. An UAV platform does not derogate to this need, but its payload has to be lighter than this installed onboard so the manufacturer needs to find an alternative to heavy sensors and navigation systems. For the georeferencing of these data, a possible solution could be to replace the Inertial Measurement Unit (IMU) by a camera and record the optical flow. The different frames would then be processed thanks to photogrammetry so as to extract the External Orientation Parameters (EOP) and, therefore, the path of the camera. The major advantages of this method called Visual Odometry (VO) is low cost, no drifts IMU-induced, option for the use of Ground Control Points (GCPs) such as on airborne photogrammetry surveys. In this paper we shall present a test bench designed to assess the reliability and accuracy of the attitude estimated from VO outputs. The test bench consists of a trolley which embeds a GNSS receiver, an IMU sensor and a camera. The LiDAR is replaced by a tacheometer in order to survey the control points already known. We have also developped a methodology applied to this test bench for the calibration of the external parameters and the computation of the surveyed point coordinates. Several tests have revealed a difference about 2–3 centimeters between the control point coordinates measured and those already known.

3D SURVEY TECHNIQUES FOR THE ARCHITECTUTAL RESTORATION: THE CASE OF ST. AGATA IN PISA

Abstract. The historical architectural heritage may be considered as the product of a complex system of interaction between several factors - cultural, socio-economic, technical, aesthetic etc. The restoration and conservation of this important heritage, therefore, requires necessarily a multidisciplinary approach, both in the preliminary phase of knowledge and in the operative one, strictly connected to the first, regarding the development of the restoration works in all their steps, from the project to the realization. The historical-critical analysis of bibliographic, archival and iconographic sources, together with the architectural survey, aims at interpreting all the events that, from the initial project to all the eventual phases of transformation, have lead the monument in its current state. This is therefore a multi-temporal and multi-spatial study in which geomatics gives an innovative contribution for its capability of gathering, storing, processing, and delivering different levels of spatially referenced information. The current techniques of architectural survey, supported by specific methodological skills, are therefore not limited to a mere mathematical-geometrical description of the historical building, but are useful also for many other purposes, such as formal-linguistic analysis, interpretation of the historical phases of transformation, description of the state of degradation/conservation etc. In this interdisciplinary perspective, photogrammetry and laser scanner represent the two main techniques, as they offer the greatest potential of performing integrated surveys. In the last decades, we have witnessed the growth and development of these 3D-survey techniques as alternative or complementary tools to the traditional ones. In particular, in the field of architectural restoration, these techniques have made significant improvements not only in terms of measure precision or reduction of time for survey operations, but also for the possibility to represent and visualize the historical building in its context. These modern techniques of survey, based on the creation of point clouds, are now widely used both in the study of a building and for the thorough description of architectural details and decorations. This paper aims at describing the methodological approach and the results of the 3D survey of the Chapel of St. Agata in Pisa, aimed at its restoration. For the development of a restoration project, the survey drawings must represent not only the geometry of a building, but also the materials and the level of degradation. So, we chose to use both the laser scanner - which guarantees uniformity of the geometric survey precision - and a 3D image-based modelling. The combined use of these two techniques, supported by a total station survey, has produced two point clouds in the same reference system, and allowed the determination of the external orientation parameters of the photographic images. Since these parameters are known, it was possible to texturize the laser scanner model with high quality images. The adopted methodology, as expected, gave back metrically correct and graphically high-quality drawings. The level of detail of the survey, and consequently of the final drawings, has been previously defined for the identification of all the elements required for the analysis of the current state, such as the clear identification and position of all the degradation phenomena, materials and decorative elements such as some fragmented and heavily damaged frescoes.

A Study on Airborne LiDAR Calibration and Operation Techniques for Bathymetric Survey

The necessity of maritime sector for continuous management, accurate and update location information such as seabed shape and location, research on airborne LiDAR bathymetry surveying techniques are accelerating. Airborne LiDAR systems consist of a scanner and GPS/INS. The location accuracy of 3D point data obtained by a LiDAR system is determined by external orientation parameters. However, there are problems in the synchronization between sensors should be performed due to a variety of sensor combinations and arrangement. To solve this issue, system calibration should be conducted. Therefore, this study evaluates the system verification methods, processes, and operation techniques.

CO-REGISTRATION OF MULTITEMPORAL UAV IMAGE DATASETS FOR MONITORING APPLICATIONS: A NEW APPROACH

Abstract. In the last years we have witnessed a rapid development of UAVs (Unmanned Aerial Vehicles), especially for image collection. One of the advantages is the possibility to perform high resolution and repeated flights in a cheap way to detect changes over time. Thus, dynamic scenes can be monitored acquiring image blocks in different epochs in a flexible way. Anyway, most of UAVs are not able to provide accurate direct geo-referencing information, so image blocks from different epochs still need to be co-registered to efficiently detect changes. This task is mostly completed using GCPs (Ground Control Points), although this approach is time consuming as manual intervention is needed. This paper aims at investigating new techniques to automate the co-registration of image blocks without the use of GCPs, just relying on an image based co-registration (IBCR) approach. The image alignment is initially performed on a reference (anchor) epoch and the registration of the following (slave) epochs is performed including some (anchor) images from the reference epoch with fixed external orientation parameters. This allows constraining the Bundle Block Adjustment of the slave epoch to be consistent with the reference one. The study involved the use of 10 multi-temporal image block over a large building construction site, and spanning a time frame of 2 years. Different tests have been performed for the reference image choice with a manual approach and then evaluating the reached accuracy. The performed tests on the chosen test site have shown that the accuracy of the proposed methodology provides results comparable to the common GCPs registration approach.

CO-REGISTRATION OF MULTITEMPORAL UAV IMAGE DATASETS FOR MONITORING APPLICATIONS: A NEW APPROACH

In the last years we have witnessed a rapid development of UAVs (Unmanned Aerial Vehicles), especially for image collection. One of the advantages is the possibility to perform high resolution and repeated flights in a cheap way to detect changes over time. Thus, dynamic scenes can be monitored acquiring image blocks in different epochs in a flexible way. <br><br> Anyway, most of UAVs are not able to provide accurate direct geo-referencing information, so image blocks from different epochs still need to be co-registered to efficiently detect changes. This task is mostly completed using GCPs (Ground Control Points), although this approach is time consuming as manual intervention is needed. <br><br> This paper aims at investigating new techniques to automate the co-registration of image blocks without the use of GCPs, just relying on an image based co-registration (IBCR) approach. The image alignment is initially performed on a reference (anchor) epoch and the registration of the following (slave) epochs is performed including some (anchor) images from the reference epoch with fixed external orientation parameters. This allows constraining the Bundle Block Adjustment of the slave epoch to be consistent with the reference one. <br><br> The study involved the use of 10 multi-temporal image block over a large building construction site, and spanning a time frame of 2 years. Different tests have been performed for the reference image choice with a manual approach and then evaluating the reached accuracy. The performed tests on the chosen test site have shown that the accuracy of the proposed methodology provides results comparable to the common GCPs registration approach.

RANGE AND IMAGE BASED MODELLING: A WAY FOR FRESCOED VAULT TEXTURING OPTIMIZATION

Abstract. In the restoration of the frescoed vaults it is not only important to know the geometric shape of the painted surface, but it is essential to document its chromatic characterization and conservation status. The new techniques of range-based and image-based modelling, each with its limitations and advantages, offer a wide range of methods to obtain the geometric shape. In fact, several studies widely document that laser scanning enable obtaining three-dimensional models with high morphological precision. However, the quality level of the colour obtained with built-in laser scanner cameras is not comparable to that obtained for the shape. It is possible to improve the texture quality by means of a dedicated photographic campaign. This procedure, however, requires to calculate the external orientation of each image identifying the control points on it and on the model through a costly step of post processing. With image-based modelling techniques it is possible to obtain models that maintain the colour quality of the original images, but with variable geometric precision, locally lower than the laser scanning model. This paper presents a methodology that uses the camera external orientation parameters calculated by image based modelling techniques to project the same image on the model obtained from the laser scan. This methodology is tested on an Italian mirror (a schifo) frescoed vault. In the paper the different models, the analysis of precision and the efficiency evaluation of proposed methodology are presented.

A Fast Recognition Algorithm for Detection of Foreign 3D Objects on a Runway

Abstract. !The systems for detection of foreign objects on a runway during the landing of an aircraft are highly demanded. Such systems could be installed in the airport or could be mounted on the board of an aircraft. This work is focused on a fast foreign object recognition algorithm for an onboard foreign object detection system. The algorithm is based on 3D object minimal boundary extraction. The boundary is estimated through an iterative process of minimization of a difference between a pair of orthophotos. During the landing an onboard camera produces a sequence of images from which a number of stereo pair could be extracted. For each frame the runway lines are automatically detected and the external orientation of the camera relative to the runway is estimated. Using external orientation parameters the runway region is projected on an orthophoto to the runway plane. The difference of orthophotos shows the objects that doesn't coincide with the runway plane. After that the position of the foreign object relative to the runway plane and its minimal 3D boundary could be calculated. The minimal 3D boundary for each object is estimated by projection of a runway region on a modified model of the runway. The extracted boundary is used for an automatic recognition of a foreign object from the predefined bank of 3D models.

Pareto optimality solution of the multi-objective photogrammetric resection-intersection problem

Reconstruction of architectural structures from photographs has recently experienced intensive efforts in computer vision research. This is achieved through the solution of nonlinear least squares (NLS) problems to obtain accurate structure and motion estimates. In Photogrammetry, NLS contribute to the determination of the 3-dimensional (3D) terrain models from the images taken from photographs. The traditional NLS approach for solving the resection-intersection problem based on implicit formulation on the one hand suffers from the lack of provision by which the involved variables can be weighted. On the other hand, incorporation of explicit formulation expresses the objectives to be minimized in different forms, thus resulting in different parametric values for the estimated parameters at non-zero residuals. Sometimes, these objectives may conflict in a Pareto sense, namely, a small change in the parameters results in the increase of one objective and a decrease of the other, as is often the case in multi-objective problems. Such is often the case with error-in-all-variable (EIV) models, e.g., in the resection-intersection problem where such change in the parameters could be caused by errors in both image and reference coordinates. This study proposes the Pareto optimal approach as a possible improvement to the solution of the resection-intersection problem, where it provides simultaneous estimation of the coordinates and orientation parameters of the cameras in a two or multistation camera system on the basis of a properly weighted multi-objective function. This objective represents the weighted sum of the square of the direct explicit differences of the measured and computed ground as well as the image coordinates. The effectiveness of the proposed method is demonstrated by two camera calibration problems, where the internal and external orientation parameters are estimated on the basis of the collinearity equations, employing the data of a Manhattan-type test field as well as the data of an outdoor, real case experiment. In addition, an architectural structural reconstruction of the Merton college court in Oxford (UK) via estimation of camera matrices is also presented. Although these two problems are different, where the first case considers the error reduction of the image and spatial coordinates, while the second case considers the precision of the space coordinates, the Pareto optimality can handle both problems in a general and flexible way.

Range Camera Self-Calibration Based on Integrated Bundle Adjustment via Joint Setup with a 2D Digital Camera

Time-of-flight cameras, based on Photonic Mixer Device (PMD) technology, are capable of measuring distances to objects at high frame rates, however, the measured ranges and the intensity data contain systematic errors that need to be corrected. In this paper, a new integrated range camera self-calibration method via joint setup with a digital (RGB) camera is presented. This method can simultaneously estimate the systematic range error parameters as well as the interior and external orientation parameters of the camera. The calibration approach is based on photogrammetric bundle adjustment of observation equations originating from collinearity condition and a range errors model. Addition of a digital camera to the calibration process overcomes the limitations of small field of view and low pixel resolution of the range camera. The tests are performed on a dataset captured by a PMD[vision]-O3 camera from a multi-resolution test field of high contrast targets. An average improvement of 83% in RMS of range error and 72% in RMS of coordinate residual, over that achieved with basic calibration, was realized in an independent accuracy assessment. Our proposed calibration method also achieved 25% and 36% improvement on RMS of range error and coordinate residual, respectively, over that obtained by integrated calibration of the single PMD camera.

A new calibration method for linear CCD camera

The linear CCD camera which applies to micro-image measuring system must have been calibrated before working. The separate calibration method of linear CCD camera’s internal and external orientation parameters is proposed in the paper. The imaging model of the linear camera has been studied, and the equal parallel lines are used to calibrate internal parameters of camera in the experiment where the industrial environment is simulated. In addition, parallel lines and tri-forked stencil are used to calibrate external orientation parameters in the industrial field, such as the attitude angel. The separate calibration method has reduced the calibration task in the industry, and the calibration template is easy to make. The results show that the testing accuracy improves greatly by using the calibrated camera for measuring the gauge, and the calibrated camera can be easily applied to other measurement environment.

On Improving Navigation Accuracy of GPS/INS Systems

Direct georeferencing, also referred to as direct platform orientation (DPO), is defined as direct measurement of the imaging sensor external orientation parameters (EOP), using positioning and orientation sensors, such as the Global Positioning System (GPS) and Inertial Navigation System (INS) or Inertial Measurement Unit (IMU). Imaging sensors, most frequently supported by the DPO technique, are digital cameras, lidar systems, multi-spectral or hyper-spectral scanners, or interferometric synthetic aperture radar (INSAR). While for scanning sensors the use of DPO is compulsory, frame digital cameras can also directly benefit from this modern technique of sensor orientation. With direct sensor orientation, the requirement for ground control, tie-point matching and aerotriangulation (AT) is significantly reduced, or even entirely eliminated, resulting in shorter times of data acquisition and processing, and streamlined and highly automated data workflow and quality control. Most of the time, the requirement for ground control points is limited to periodic system calibrations and quality control check. Direct georeferencing is considered a fundamental technology of conventional mobile mapping systems (MMS). Despite significant progress in GSP/INS-based direct georeferencing technology in the last decade, there is still room for improvement in terms of better accuracy and better tolerance to GPS outages. This paper is focused on three error modeling and compensation techniques that could potentially improve GPS/INS system's performance on both land-based and airborne platforms: (1) extended gravity compensation, (2) IMU signal de-noising, and (3) stochastic modeling of IMU errors.