Hierarchical structure-and-motion recovery from uncalibrated images

This paper addresses the structure-and-motion problem, that requires to find camera motion and 3D struc- ture from point matches. A new pipeline, dubbed Samantha, is presented, that departs from the prevailing sequential paradigm and embraces instead a hierarchical approach. This method has several advantages, like a provably lower computational complexity, which is necessary to achieve true scalability, and better error containment, leading to more stability and less drift. Moreover, a practical autocalibration procedure allows to process images without ancillary information. Experiments with real data assess the accuracy and the computational efficiency of the method.Comment: Accepted for publication in CVI

Development of a Computer Vision-Based Three-Dimensional Reconstruction Method for Volume-Change Measurement of Unsaturated Soils during Triaxial Testing

Problems associated with unsaturated soils are ubiquitous in the U.S., where expansive and collapsible soils are some of the most widely distributed and costly geologic hazards. Solving these widespread geohazards requires a fundamental understanding of the constitutive behavior of unsaturated soils. In the past six decades, the suction-controlled triaxial test has been established as a standard approach to characterizing constitutive behavior for unsaturated soils. However, this type of test requires costly test equipment and time-consuming testing processes. To overcome these limitations, a photogrammetry-based method has been developed recently to measure the global and localized volume-changes of unsaturated soils during triaxial test. However, this method relies on software to detect coded targets, which often requires tedious manual correction of incorrectly coded target detection information. To address the limitation of the photogrammetry-based method, this study developed a photogrammetric computer vision-based approach for automatic target recognition and 3D reconstruction for volume-changes measurement of unsaturated soils in triaxial tests. Deep learning method was used to improve the accuracy and efficiency of coded target recognition. A photogrammetric computer vision method and ray tracing technique were then developed and validated to reconstruct the three-dimensional models of soil specimen

Robust and large-scale quasiconvex programming in structure-from-motion

Structure-from-Motion (SfM) is a cornerstone of computer vision. Briefly speaking, SfM is the task of simultaneously estimating the poses of the cameras behind a set of images of a scene, and the 3D coordinates of the points in the scene. Often, the optimisation problems that underpin SfM do not have closed-form solutions, and finding solutions via numerical schemes is necessary. An objective function, which measures the discrepancy of a geometric object (e.g., camera poses, rotations, 3D coordi- nates) with a set of image measurements, is to be minimised. Each image measurement gives rise to an error function. For example, the reprojection error, which measures the distance between an observed image point and the projection of a 3D point onto the image, is a commonly used error function. An influential optimisation paradigm in SfM is the ℓ₀₀ paradigm, where the objective function takes the form of the maximum of all individual error functions (e.g. individual reprojection errors of scene points). The benefit of the ℓ₀₀ paradigm is that the objective function of many SfM optimisation problems become quasiconvex, hence there is a unique minimum in the objective function. The task of formulating and minimising quasiconvex objective functions is called quasiconvex programming. Although tremendous progress in SfM techniques under the ℓ₀₀ paradigm has been made, there are still unsatisfactorily solved problems, specifically, problems associated with large-scale input data and outliers in the data. This thesis describes novel techniques to tackle these problems. A major weakness of the ℓ₀₀ paradigm is its susceptibility to outliers. This thesis improves the robustness of ℓ₀₀ solutions against outliers by employing the least median of squares (LMS) criterion, which amounts to minimising the median error. In the context of triangulation, this thesis proposes a locally convergent robust algorithm underpinned by a novel quasiconvex plane sweep technique. Imposing the LMS criterion achieves significant outlier tolerance, and, at the same time, some properties of quasiconvexity greatly simplify the process of solving the LMS problem. Approximation is a commonly used technique to tackle large-scale input data. This thesis introduces the coreset technique to quasiconvex programming problems. The coreset technique aims find a representative subset of the input data, such that solving the same problem on the subset yields a solution that is within known bound of the optimal solution on the complete input set. In particular, this thesis develops a coreset approximate algorithm to handle large-scale triangulation tasks. Another technique to handle large-scale input data is to break the optimisation into multiple smaller sub-problems. Such a decomposition usually speeds up the overall optimisation process, and alleviates the limitation on memory. This thesis develops a large-scale optimisation algorithm for the known rotation problem (KRot). The proposed method decomposes the original quasiconvex programming problem with potentially hundreds of thousands of parameters into multiple sub-problems with only three parameters each. An efficient solver based on a novel minimum enclosing ball technique is proposed to solve the sub-problems.Thesis (Ph.D.) (Research by Publication) -- University of Adelaide, School of Computer Science, 201

Prediction and visualisation of bony impingement for subject specific total hip arthroplasty

Bony impingement (BI) may contribute to restricted hip joint motion, and recurrent dislocation after total hip arthroplasty (THA), and therefore, should be avoided where possible. However, BI risk assessment is generally performed intra-operatively by surgeons, which is partially subjective and qualitative. Therefore, the aim of the study was to develop a method for identifying subject-specific BI, and subsequently, visualising BI area on native bone anatomy to highlight the amount of bone should be resected. Activity definitions and subject-specific bone geometries, constructed from CT scans, with planned implants were used as inputs for the method. For each activity, a conical clearance angle (CCA) was checked between femur and pelvis through simulation. Simultaneously, BI boundary and area were automatically calculated using ray intersection and region growing algorithm respectively. The potential use of the developed method was explained through a case study using an anonymised pre-THA patient data. Two pure (flexion, and extension) and two combined hip joint motions (internal and external rotation at flexion and extension respectively) were considered as activities. BI area were represented in two ways: (a) CCA specific where BI area for each activity with different CCAs was highlighted, (b) activity specific where BI area for all activities with a particular CCA was presented. Result showed that BI area between the femoral and pelvic parts was clearly identified so that the pre-operative surgical plan could be adjusted to minimise impingement. Therefore, this method could potentially be used to examine the effect of different preoperative plans and hip motion on BI, and to guide bony resection during THA surgery

A New Three Object Triangulation Algorithm for Mobile Robot Positioning

Positioning is a fundamental issue in mobile robot applications. It can be achieved in many ways. Among them, triangulation based on angles measured with the help of beacons is a proven technique. Most of the many triangulation algorithms proposed so far have major limitations. For example, some of them need a particular beacon ordering, have blind spots, or only work within the triangle defined by the three beacons. More reliable methods exist; however, they have an increasing complexity or they require to handle certain spatial arrangements separately. In this paper, we present a simple and new three object triangulation algorithm, named ToTal, that natively works in the whole plane, and for any beacon ordering. We also provide a comprehensive comparison between many algorithms, and show that our algorithm is faster and simpler than comparable algorithms. In addition to its inherent efficiency, our algorithm provides a very useful and unique reliability measure, assessable anywhere in the plane, which can be used to identify pathological cases, or as a validation gate in Kalman filters.Peer reviewe

The design of a digital photogrammetric metrology system for the semi-automated surveying and recording of pipe dimensions in industrial plants

Bibliography: pages 51-53.This thesis reports on the design, development and testing of a semi-automated system to aid in the mapping of the interior of industrial plants. The system makes use of digital photogrammetry to assist an operator in locating and identifying components of the plants. All of the important photogrammetric theory is discussed in the text, and explained in detail in the appendices. Specifically, this system implements various algorithms used for camera calibration, object point intersection, and a method combining the two techniques. Considerable use is made of the iterative least squares method, which is the basis of many of the algorithms employed in this work. Image processing algorithms are implemented to enhance the digital images, and to ease the identification of objects in the images, and these are fully explained in the text. Adaptive least squares image matching is a method of matching corresponding points in different images and is used to ensure correspondence between points identified by the system operator. A weighted centre of gravity method is used to find the centre of target areas, and an algorithm is implemented to determine the radius, centre and direction of a pipe passing through a number of points. Various aspects of the system design are discussed and explained. In particular the requirements in terms of hardware and software are presented. In addition, the choices of the operating system and of the compiler are justified. Potential problems with the system, and possible enhancements of it are also described. Tests were performed to verify the correct operation of all of the algorithms used in the calibration of the cameras. Together with the point intersection routines, these tests calculated the position of various control points, the correct coordinates of which were previously known. The calculated point positions are compared to the known coordinates of the points to determine the accuracy of the various algorithms. Further tests were conducted to demonstrate and verify the ability of the system to measure distance in three dimensions. These tests illustrate that the accuracy achievable is approximately 0.053 of the total distance measured for an object occupying 803 of the width of the image. The system improves considerably on the method presently used in South Africa and in many industries worldwide which rely on analytical photogrammetry for the determination of object point locations. While the system suffers from reduced accuracy as a result of the use of digital cameras, this problem will become less important as technology and digital camera resolution improve. Possible enhancements include the use of more numerically efficient algorithms, and the introduction of techniques that would partially automate the identification of control points and pipes

Affine multi-view modelling for close range object measurement

In photogrammetry, sensor modelling with 3D point estimation is a fundamental topic of research. Perspective frame cameras offer the mathematical basis for close range modelling approaches. The norm is to employ robust bundle adjustments for simultaneous parameter estimation and 3D object measurement. In 2D to 3D modelling strategies image resolution, scale, sampling and geometric distortion are prior factors. Non-conventional image geometries that implement uncalibrated cameras are established in computer vision approaches; these aim for fast solutions at the expense of precision. The projective camera is defined in homogeneous terms and linear algorithms are employed. An attractive sensor model disembodied from projective distortions is the affine. Affine modelling has been studied in the contexts of geometry recovery, feature detection and texturing in vision, however multi-view approaches for precise object measurement are not yet widely available. This project investigates affine multi-view modelling from a photogrammetric standpoint. A new affine bundle adjustment system has been developed for point-based data observed in close range image networks. The system allows calibration, orientation and 3D point estimation. It is processed as a least squares solution with high redundancy providing statistical analysis. Starting values are recovered from a combination of implicit perspective and explicit affine approaches. System development focuses on retrieval of orientation parameters, 3D point coordinates and internal calibration with definition of system datum, sensor scale and radial lens distortion. Algorithm development is supported with method description by simulation. Initialization and implementation are evaluated with the statistical indicators, algorithm convergence and correlation of parameters. Object space is assessed with evaluation of the 3D point correlation coefficients and error ellipsoids. Sensor scale is checked with comparison of camera systems utilizing quality and accuracy metrics. For independent method evaluation, testing is implemented over a perspective bundle adjustment tool with similar indicators. Test datasets are initialized from precise reference image networks. Real affine image networks are acquired with an optical system (~1M pixel CCD cameras with 0.16x telecentric lens). Analysis of tests ascertains that the affine method results in an RMS image misclosure at a sub-pixel level and precisions of a few tenths of microns in object space

Metric aspects of reconnaissance frame photography

No abstract available