A subsonic wind tunnel facility was built and tested as part of a base line test investigating flow within a diffuser-collector. Facility controls allowed the quarter scale model to match both Reynolds number and Mach number. Mass averaged conditions at the diffuser inlet during testing were determined as 1.939 ? 106 for Reynolds number based upon diffuser inlet hydraulic diameter, and 0.418 for Mach number. A flow conditioning section prior to test section contained several interchangeable sections. Flow conditioning components were used to create flow characteristic of that leaving the last stage of a land-based gas turbine. The diffuser-collector subsystem was evaluated through the use of wall static pressure measurements, a variety of probe traverse measurements, and Stereo-PIV. Flow within the collector and diffuser were determined to be heavily dependent upon the collector geometry. PIV measurements showed the development of two large counter rotating vortices within the collector. Each symmetric vortex grew and shifted according to the collector geometry while creating complex regions of flow. Pressure recovery within the diffuser was in range of 0.47 to 0.78, and would drop to 0.52 at the collector exit. The drop in pressure recovery was presumed to be a combination of inefficient diffusion in the collector and losses due to the vortices. The baseline test was found to be successful in terms of facility design, and determining the critical flow phenomena. Further testing and experimentation are necessary to evaluate specific details of the collector geometry's effect upon the pressure recovery and flow development. / Master of Science

There is a great need in real world applications for estimating depth through electronic means without human intervention. There are many methods in the field which help in autonomously finding depth measurements. Some of which are using LiDAR, Radar, etc. One of the most researched topic in the field of depth measurements is Computer Vision which uses techniques on 2D images to achieve the desired result. Out of the many 3D vision techniques used, stereovision is a field where a lot of research is being done to solve this kind of problem. Human vision plays an important part behind the inspiration and research performed in this field. Stereovision gives a very high spatial resolution of depth estimates which is used for obstacle avoidance, path planning, object recognition, etc. Stereovision makes use of two images in the image pair. These images are taken with two cameras from different views and those two images are processed to get depth information. Processing stereo images has been one of the most intensively sought-after research topics in computer vision. Many factors affect the performance of this approach like computational efficiency, depth discontinuities, lighting changes, correspondence and correlation, electronic noise, etc. An algorithm is proposed which uses texture features obtained using Laws Energy Masks and multi-block approach to perform correspondence matching between stereo pair of images with high baseline. This is followed by forming disparity maps to get the relative depth of pixels in the image. An analysis is also made between this approach to the current state-of-the-art algorithms. A robust method to score and rank the stereo algorithms is also proposed. This approach provides a simple way for researchers to rank the algorithms according to their application needs. / Master of Science

Presently, aerial photography remains a popular method for surveillance of landscapes, and its uses continually grow as it is used to monitor trends in areas such as plant distribution and urban construction. The use of computer vision, or more specifically stereo vision, is one common method of gathering this information. By mounting a stereo vision system on the wings of an unmanned aircraft it becomes very useful tool. This technique however, becomes less accurate as stereo vision baselines become longer, aircraft wing spans are increased, and aircraft wings become increasingly flexible. Typically, ideal stereo vision systems involve stationary cameras with parallel fields of view. For an operational aircraft with a stereo vision system installed, stationary cameras can not be expected because the aircraft will experience random atmospheric turbulence in the form of gusts that will excite the dominate frequencies of the aircraft. A method of stereo image rectification has been developed for cases where cameras that will be allowed to deflect on the wings of an fixed wing aircraft that is subjected to random excitation. The process begins by developing a dynamic model the estimates the behavior of a flexible stereo vision system and corrects images collected at maximum deflection. Testing of this method was performed on a flexible stereo vision system subjected to resonance excitation where a reduction in stereo vision distance error is shown. Successful demonstration of this ability is then repeated on a flying wing aircraft by the using a modal survey to understand its behavior. Finally, the flying wing aircraft is subjected to random excitation and a least square fit of the random excitation signal is used to determine points of maximum deflection suitable for stereo image rectification. Using the same techniques for image rectification in resonance excitation, significant reductions in stereo distance errors are shown. / Master of Science

The robotics field has grown in recent years to a point where unmanned systems are no longer limited by their capabilities. As such, the mission profiles for unmanned systems are becoming more and more complicated, and a demand has risen for the deployment of unmanned systems into the most complex of environments. Additionally, the objectives for unmanned systems are once more complicated by the necessity for beyond line of sight teleoperation, and in some cases complete vehicle autonomy. Such systems require adequate sensory devices for appropriate situational awareness. Additionally, a large majority of what is currently being done with unmanned systems requires visual data acquisition. A stereo vision system is ideal for such missions as it doubles as both an image acquisition device, and a range finding device. The 2D images captured with a stereo vision system can be mapped to three dimensional point clouds with reference to the optic center of one of the stereo cameras. While stand alone commercial stereo vision systems are capable of doing just that, the GPS/INS aided stereo vision system also has integrated 3-axis accelerometers, 3-axis gyros, 3-axis magnetometer, and GPS receiver allowing for the measurement of the system's position and orientation in global coordinates. This capability provides the potential to geo-reference the 3D data captured with the stereo camera. The GPS/INS aided stereo vision system integrates a combination of commercial and in-house developed devices. The total system includes a Point Grey Research Bumblebee stereovision camera, a Versalogic PC104 computer, a PCB designed for sensor acquisition and power considerations, and a self contained battery. The entire system is all contained within a 9.5â x 5â x 6.5â aluminum enclosure and weighs approximately 6 lbs. The system is also accompanied with a graphical user interface which displays the geo-referenced data within a 3D virtual environment providing adequate sensor feedback for a teleoperated unmanned vehicle. This thesis details the design and implementation of the hardware and software included within this system as well as the results of operation. / Master of Science

Conventional stereo vision systems rely on two spatially fixed cameras to gather depth information about a scene. The cameras typically have a fixed distance between them, known as the baseline. As the baseline increases, the estimated 3D information becomes more accurate, which makes it advantageous to have as large a baseline as possible. However, large baselines have problems whenever objects approach the cameras. The objects begin to leave the field of view of the cameras, making it impossible to determine where they are located in 3D space. This becomes especially important if an object of interest must be actuated upon and is approached by a vehicle. In an attempt to overcome this limitation, this thesis introduces a variable baseline stereo system that can adjust its baseline automatically based on the location of an object of interest. This allows accurate depth information to be gathered when an object is both near and far. The system was designed to operate under, and automatically move to a large range of different baselines. This thesis presents the mechanical design of the stereo boom. This is followed by a derivation of a control scheme that adjusts the baseline based on an estimate object location, which is gathered from stereo vision. This algorithm ensures that a certain incident angle on an object of interest is never surpassed. This maximum angle is determined by where a stereo correspondence algorithm, Semi-Global Block Matching, fails to create full reconstructions. / Master of Science

When considering the operation of an Unmanned Aerial Vehicle (UAV) or an Unmanned Ground Vehicle (UGV), such problems as landing site estimation or robot path planning become a concern. Deciding if an area of terrain has a level enough slope and a wide enough area to land a Vertical Take Off and Landing (VTOL) UAV or if an area of terrain is traversable by a ground robot is reliant on data gathered from sensors, such as cameras. 3-D models, which can be built from data extracted from digital cameras, can help facilitate decision making for such tasks by providing a virtual model of the surrounding environment the system is in. A stereo vision system utilizes two or more cameras, which capture images of a scene from two or more viewpoints, to create 3-D point clouds. A point cloud is a set of un-gridded 3-D points corresponding to a 2-D image, and is used to build gridded surface models. Designing a stereo system for distant terrain modeling requires an extended baseline, or distance between the two cameras, in order to obtain a reasonable depth resolution. As the width of the baseline increases, so does the flexibility of the system, causing the orientation of the cameras to deviate from their original state. A set of tools have been developed to generate 3-D point clouds from rigid and flexible stereo systems, along with a method for applying corrections to a flexible system to regain distance accuracy in a flexible system. / Master of Science

Yes / Purpose: The purpose of this study was to develop a convenient test of stereopsis in the clinic that is both robust and reliable and capable of providing a measure of variability necessary to make valid comparisons between measurements obtained at different occasions or under different conditions. Methods: Stereo acuity was measured based on principles derived from the laboratory measurement of stereopsis (i.e., staircase method). Potential premeasurement compensations are described if there is a significant degree of ocular misalignment, reduced visual acuity, or aniseikonia. Forty-six adults at McGill University, 44 adults at Auckland University, and 51 adults from the University of Bradford, with an age range of 20 to 65 years old and normal or corrected-to-normal vision participated in this study. Results: Stereo acuity within this normal population was widely distributed, with a significant percentage (28%) of the population with only coarse stereo (>300 arc seconds). Across subjects, the SD was approximately 25% of the mean. Measurements at two different times were strongly (r = 0.79) and significantly (P < 0.001) correlated, with little to no significant (P = 0.79) bias (0.01) between test and retest measures of stereopsis. Conclusions: The application enables measurements over the wide disparity range and not just at the finest disparities. In addition, it allows changes in stereopsis of the order of 1.9 to be statistically distinguished.

Yes / Designed as a pragmatic approach that anticipates change to cultural heritage, this chapter discusses responses that encompass records for tangible cultural heritage (monuments, sites and landscapes) and the narratives that see the impact upon them. The Curious Travellers project provides a mechanism for digitally documenting heritage sites that have been destroyed or are under immediate threat from unsympathetic development, neglect, natural disasters, conflict and cultural vandalism. The project created and tested data-mining and crowd-sourced workflows that enable the accurate digital documentation and 3D visualisation of buildings, archaeological sites, monuments and heritage at risk. When combined with donated content, image data are used to recreate 3D models of endangered and lost monuments and heritage sites using a combination of open-source and proprietary methods. These models are queried against contextual information, helping to place and interrogate structures with relevant site and landscape data for the surrounding environment. Geospatial records such as aerial imagery and 3D mobile mapping laser scan data serve as a framework for adding new content and testing accuracy. In preserving time-event records, image metadata offers important information on visitor habits and conservation pressures, which can be used to inform measures for site management. / The Curious Travellers project was funded as a component of the AHRC Digital Transformations Theme Large Grant ‘Fragmented Heritage’ (AH/L00688X/1). AHRC Follow-on funding has seen this approach contribute to the BReaTHe project (AH/S005951/1) which seeks to Build Resilience Through Heritage for displaced communities and with a contribution to the BA Cities and Infrastructures Scheme project, ‘Reducing Disaster Risk to Life and Livelihoods by evaluating the seismic performance of retrofitted interventions within Kathmandu’s UNESCO World Heritage Site during the 2015 Earthquake’, with Durham University (KF1\100109).

This thesis deals with the problem of three dimensional scene reconstruction from multiple camera images. This is a well established problem in computer vision and has been significantly researched. In recent years some excellent results have been achieved, however existing algorithms often fall short of many biological systems in terms of robustness and generality. The aim of this research was to develop improved algorithms for reconstructing 3D scenes, with a focus on accurate system modelling and correctly dealing with occlusions. With scene reconstruction the objective is to infer scene parameters describing the 3D structure of the scene from the data given by camera images. This is an illposed inverse problem, where an exact solution cannot be guaranteed. The use of a statistical approach to deal with the scene reconstruction problem is introduced and the differences between maximum a priori (MAP) and minimum mean square estimate (MMSE) considered. It is discussed how traditional stereo matching can be performed using a volumetric scene model. An improved model describing the relationship between the camera data and a discrete model of the scene is presented. This highlights some of the common causes of modelling errors, enabling them to be dealt with objectively. The problems posed by occlusions are considered. Using a greedy algorithm the scene is progressively reconstructed to account for visibility interactions between regions and the idea of a complete scene estimate is established. Some simple and improved techniques for reliably assigning opaque voxels are developed, making use of prior information. Problems with variations in the imaging convolution kernel between images motivate the development of a pixel dissimilarity measure. Belief propagation is then applied to better utilise prior information and obtain an improved global optimum. A new volumetric factor graph model is presented which represents the joint probability distribution of the scene and imaging system. By utilising the structure of the local compatibility functions, an efficient procedure for updating the messages is detailed. To help convergence, a novel approach of accentuating beliefs is shown. Results demonstrate the validity of this approach, however the reconstruction error is similar or slightly higher than from the Greedy algorithm. To simplify the volumetric model, a new approach to belief propagation is demonstrated by applying it to a dynamic model. This approach is developed as an alternative to the full volumetric model because it is less memory and computationally intensive. Using a factor graph, a volumetric known visibility model is presented which ensures the scene is complete with respect to all the camera images. Dynamic updating is also applied to a simpler single depth-map model. Results show this approach is unsuitable for the volumetric known visibility model, however, improved results are obtained with the simple depth-map model.

Kompiuterinė erdvinė rega - tai erdvinės informacijos gavimas iš skaitmeninių vaizdų. Ši mokslo sritis yra ganėtinai nauja ir jos populiarumas auga. Kompiuterinė erdvinė rega naudojama robotikoje, pramonėje, buityje ir kitose srityse. Pagrindinis magistro darbo tikslas yra išanalizuoti ir palyginti erdvinio vaizdo algoritmus. Šiam tikslui pasiekti yra keliami šie uždaviniai: suklasifikuoti erdvinio vaizdo algoritmus, apžvelgti jų sudarymo metodus, sukurti erdvinio vaizdo algoritmų įvertinimo metodiką ir vadovaujantis ja įvertinti erdvinio vaizdo algoritmus. Vadovaujantis kitų autorių moksliniais darbais, erdvinės regos algoritmai, pagal jų veikimo principus buvo suklasifikuoti ir išskirti i dvi grupės: lokalinius ir globalius. Iš kiekvienos grupės buvo išskirti keli algoritmai, su kuriais ir buvo atliekamas tyrimas. Iš lokalinių buvo išrinktas bazinis lokalinis algoritmas su skirtingais matematiniais sprendimais, o iš globalių buvo paimtas dinaminis programavimas. Išvardintų algoritmų palyginimui buvo sukurta įvertinimo metodika. Pagrindiniai jos kriterijai yra koreliacijos koeficientas ir algoritmo atlikimo laikas. Visi išvardinti algoritmai buvo išbandyti vadovaujantis įvertinimo metodika. Remiantis bandymų rezultatais ir metodika buvo išrinkti geriausi rezultatai. Atliktų eksperimentinių tyrimų rezultatai parodo, kad išbandyti algoritmai nėra tobuli, bet ir jie tinka vartojimui, nors ir su tam tikrais apribojimais. Taip pat algoritmų netobulumas parodo, kad ne... [toliau žr. visą tekstą] / Computer stereo vision is a receiving of stereo information from digital images. This field of science is rather new and its popularity is increasing rapidly. Computer stereo vision is applied in robotics, manufacturing industry, everyday life and other spheres. The aim of the Thesis is to analyze and compare the stereo vision algorithms. In order to achieve the aim of the Research, the following tasks are determined: to classify the stereo vision algorithms, to study the methods of algorithm design, to create the method of assessment of stereo vision algorithms and to assess the stereo vision algorithms basing on the ground of this method. Basing on academic works of various authors, the stereo vision algorithms are classified and divided into two groups in accordance with the modes of their functioning: local and global algorithms. Several algorithms are chosen from each group. A based local algorithm with different mathematical solutions is chosen from the group of local algorithms, and the dynamic programming is chosen from the group of the global algorithms. The chosen algorithms are tested in the course of the Research. To compare the mentioned algorithms, the assessment method is prepared, the main criteria of which are the correlation index and the running time of algorithm. All abovementioned algorithms are tested by the means of the method of assessment. The best results are chosen basing on the method and results of the tests. The results of the conducted... [to full text]