Densely-sampled light field reconstruction

In this chapter, we motivate the use of densely-sampled light fields as the representation which can bring the required density of light rays for the correct recreation of 3D visual cues such as focus and continuous parallax and can serve as an intermediary between light field sensing and light field display. We consider the problem of reconstructing such a representation from few camera views and approach it in a sparsification framework. More specifically, we demonstrate that the light field is well structured in the set of so-called epipolar images and can be sparsely represented by a dictionary of directional and multi-scale atoms called shearlets. We present the corresponding regularization method, along with its main algorithm and speed-accelerating modifications. Finally, we illustrate its applicability for the cases of holographic stereograms and light field compression.acceptedVersionPeer reviewe

Visibility and acceptance of discrete-sampling artifacts in visual displays

Ph. D. ThesisDigital visual displays are aimed to provide an illusion of a continuous reality through a discrete presentation of visual information. This thesis explored three topics on (i) angular, (ii) spatial, and (iii) temporal sampling characteristics, related to distortion visibility, acceptance, and discomfort. In the first topic, we addressed the issue of optimizing the view density in continuous parallax visualization by replicating the changing views of a 3-D object for a moving observer. We measured the visibility of the related artifacts and evaluated the performance of full-reference visual quality metrics. We found that the state-of-the-art metrics can indirectly characterize artifact visibility and established a quantitative relationship for threshold estimation on varying conditions. The second topic addressed the relation of the contrast sensitivity function (CSF) to adaptation luminance and specifically its asymptotic behavior at high light levels essential to modern high-luminance displays. Using a custombuilt system, we measured the CSF at relatively high luminance levels and spatial frequency range, integrating our dataset to the existing research. We found a gradual transition among the linear to DeVries-Rose to Weber regions with steeper slopes for higher frequencies and lower luminance. A further decreasing region was located at low to intermediate frequencies. Following this construct, we adopted a model consisting of central elements in the visual signal processing and proposed an eight-parameter form for the CSF in the luminance domain. The final topic addressed the effects of frame rate on distortion acceptance and its impact on visual discomfort during regular display use. We assessed the perceived symptoms, preference, and task performance under varying conditions. The measurements indicated that for nondemanding everyday tasks, the frame rate could be reasonably reduced without severe effects on the observer; however, this tolerance diminished under more dynamic content. A potential association of discomfort with the blinking activity was also discussedThe European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No 676401, European Training Network on Full Parallax Imaging and Huawei Technologies Co., Lt

Laser Based Altimetry for Unmanned Aerial Vehicle Hovering Over a Snow Surface

A microwave radar for non-invasive snow stratigraphy measurements has been developed. Results were promising, but it failed to detect light powder snow in the air-snowpack interface. The aim of this thesis is to find and verify a system for estimating altitude on centimeter scale over a snow surface, independent of snow conditions. Also, relative pitch and roll angle estimation between the UAV and local surface should be resolved, to help directing the radar beam perpendicularly to the surface. After a variety of technical solutions were examined, we propose a system of three time-of-flight near-infrared altimeters pointing at different directions towards the surface. Experimental results showed RMS error of 1.39 cm for range estimation averaged over the most common snow types, and 2.81 cm for wet snow, which was the least reflective medium. An experiment conducted for an array of two altimeters scanning over a snow surface, showed that the local, relative surface tilt was found to be accurate within ±2° given that it was sufficiently planar. Further, the altitude RMS error was estimated to 1.57 cm. We conclude that the chosen altimeter was within the requirements, and that an array of three altimeters would give acceptable relative tilt estimation in to planes on the snow surface. The system should be subject to flight testing and implemented on UAV platform such that it can aid the microwave radar system during snow scanning

Confidence and feedback in visual perceptual learning

The classical view that perceptual learning is highly specific to the stimulus properties used during training is being challenged by accumulating evidence of transfer under specific conditions. Perceptual learning in the adult brain may result from an element of cortical reorganisation at a perceptual level or a reorganisation of decision weights at a higher level. This thesis focuses on individual differences in perception, and the mechanisms of perceptual learning. Since the role of feedback is not usually the primary area of interest for perceptual learning research, this was one of the main focus points of the methodology used. Perception and perceptual learning were assessed for a range of tasks at local and global levels, including depth perception in random dot stereograms, and global motion and form coherence. The results of these experiments established that transfer occurred when the task matched the tuning of the global processing area, even when the untrained task was a locally processed task. The results also provided evidence of robust learning in local and global tasks with or without feedback, as long as easy and difficult trials were interleaved within the same task. Furthermore, in some conditions internal feedback provided better learning at sub-threshold stimulus levels than did explicit external feedback. These results suggest that, for low stimulus intensities, external feedback may reduce observers' confidence in their own perceptual decisions. Confidence in perceptual decisions was a key factor throughout all the studies, and where this was measured it was found to be highly correlated with performance. Confidence in perceptual decision and accuracy was low for a depth perception study using anti-correlated random-dot stereogram (ACRDS). The binocular energy model of neural responses predicts that depth from binocular disparity may be perceived in the reversed-direction when the contrast of dots are anti-correlated. Depth was mostly perceived in the correct direction for ACRDS conditions with some inconsistencies. These differences are likely to reflect the inconsistent depth signals, across scale and across first- and second-order channels, elicited by anticorrelated stimuli. To ensure that the rich variability embedded within the individual differences in heterogeneous data sets were not excluded from analyses, mixed effects models were employed throughout the thesis. This technique considers between-individual variation as a random factor which made it possible to investigate behavioural differences between individuals with migraine and control groups. Specifically we evaluated the spatial extent of excitatory and inhibitory interactions using a classic lateral masking task. Overall, contrast thresholds in the baseline condition for the migraine group were lower than those in the control group. There was no difference in the degree of lateral interaction in the migraine group. The results suggest the that impaired performance in perceptual tasks in individuals with migraine may not be as a results of altered local mechanisms

Standing on the Shoulders of Giants: New Mass and Distance Estimates for Betelgeuse through Combined Evolutionary, Asteroseismic, and Hydrodynamic Simulations with MESA

We conduct a rigorous examination of the nearby red supergiant Betelgeuse by drawing on the synthesis of new observational data and three different modeling techniques. Our observational results include the release of new, processed photometric measurements collected with the space-based Solar Mass Ejection Imager instrument prior to Betelgeuse's recent, unprecedented dimming event. We detect the first radial overtone in the photometric data and report a period of 185 ± 13.5 days. Our theoretical predictions include self-consistent results from multi-timescale evolutionary, oscillatory, and hydrodynamic simulations conducted with the Modules for Experiments in Stellar Astrophysics software suite. Significant outcomes of our modeling efforts include a precise prediction for the star's radius: 764_(-62)^(+116),R_⊙. In concert with additional constraints, this allows us to derive a new, independent distance estimate of 168_(-15)^(+27) pc and a parallax of π = 5.95_(-0.85)^(+0.58) mas, in good agreement with Hipparcos but less so with recent radio measurements. Seismic results from both perturbed hydrostatic and evolving hydrodynamic simulations constrain the period and driving mechanisms of Betelgeuse's dominant periodicities in new ways. Our analyses converge to the conclusion that Betelgeuse's ≈400 day period is the result of pulsation in the fundamental mode, driven by the κ-mechanism. Grid-based hydrodynamic modeling reveals that the behavior of the oscillating envelope is mass-dependent, and likewise suggests that the nonlinear pulsation excitation time could serve as a mass constraint. Our results place α Orionis definitively in the early core helium-burning phase of the red supergiant branch. We report a present-day mass of 16.5–19 M_⊙—slightly lower than typical literature values

Evaluation of Image Based Techniques for Wildfire Detection and Fuel Mapping

Few events can cause the catastrophic impact to ecology, infrastructure, and human safety of a wildland fire along the wildland urban interface. The suppression of natural wildland fires over the past decade has caused a buildup of dry, dead surface fuels: a condition that, coupled with the right weather conditions, can cause large destructive wildfires that are capable of threatening both ancient tree stands and manmade infrastructure. Firefighters use fire danger models to determine staffing needs on high fire risk days; however models are only as effective as the spatial and temporal density of their observations. OKFIRE, an Oklahoma initiative created by a partnership between Oklahoma State University and the University of Oklahoma, has proven that fire danger assessments close to the fire � both geographically and temporally � can give firefighters a significant increase in their situational awareness while fighting a wildland fire.This paper investigates several possible solutions for a small Unmanned Aerial System (UAS) which could gather information useful for detecting ground fires and constructing fire danger maps. Multiple fire detection and fuel mapping programs utilize satellites, manned aircraft, and large UAS equipped with hyperspectral sensors to gather useful information. Their success provides convincing proof of the utility that could be gained from low-altitude UAS gathering information at the exact time and place firefighters and land managers are interested in. Close proximity, both geographically and operationally, to the end can reduce latency times below what could ever be possible with satellite observation.This paper expands on recent advances in computer vision, photogrammetry, and infrared and color imagery to develop a framework for a next-generation UAS which can assess fire danger and aid firefighters in real time as they observe, contain, or extinguish wildland fires. It also investigates the impact information gained by this system could have on pre-fire risk assessments through the development of very high resolution fuel maps.Mechanical & Aerospace Engineerin

Natural freehand grasping of virtual objects for augmented reality

Grasping is a primary form of interaction with the surrounding world, and is an intuitive interaction technique by nature due to the highly complex structure of the human hand. Translating this versatile interaction technique to Augmented Reality (AR) can provide interaction designers with more opportunities to implement more intuitive and realistic AR applications. The work presented in this thesis uses quantifiable measures to evaluate the accuracy and usability of natural grasping of virtual objects in AR environments, and presents methods for improving this natural form of interaction. Following a review of physical grasping parameters and current methods of mediating grasping interactions in AR, a comprehensive analysis of natural freehand grasping of virtual objects in AR is presented to assess the accuracy, usability and transferability of this natural form of grasping to AR environments. The analysis is presented in four independent user studies (120 participants, 30 participants for each study and 5760 grasping tasks in total), where natural freehand grasping performance is assessed for a range of virtual object sizes, positions and types in terms of accuracy of grasping, task completion time and overall system usability. Findings from the first user study in this work highlighted two key problems for natural grasping in AR; namely inaccurate depth estimation and inaccurate size estimation of virtual objects. Following the quantification of these errors, three different methods for mitigating user errors and assisting users during natural grasping were presented and analysed; namely dual view visual feedback, drop shadows and additional visual feedback when adding user based tolerances during interaction tasks. Dual view visual feedback was found to significantly improve user depth estimation, however this method also significantly increased task completion time. Drop shadows provided an alternative, and a more usable solution, to dual view visual feedback through significantly improving depth estimation, task completion time and the overall usability of natural grasping. User based tolerances negated the fundamental problem of inaccurate size estimation of virtual objects, through enabling users to perform natural grasping without the need of being highly accurate in their grasping performance, thus providing evidence that natural grasping can be usable in task based AR environments. Finally recommendations for allowing and further improving natural grasping interaction in AR environments are provided, along with guidelines for translating this form of natural grasping to other AR environments and user interfaces

The Development, Validation, and Application of the Eelgrass Health Index

Eelgrass (Zostera marina L) provides essential habitat and forage for waterbirds, fish, and other coastal marine species, nutrient and sediment capture which improves water quality, carbon storage, and wave energy buffering which reduces coastal erosion. Changes in its health can indicate other coastal ecosystem changes. Since the 1980s, eelgrass beds have declined in James Bay, Québec. The eelgrass decline coincided with a decrease in the abundance of migratory Brant and Canada geese visiting the coastal eelgrass meadows, which the geese rely on for forage during their spring and fall migrations. Geese are important species to the coastal First Nation Cree communities of Québec and are harvested by the Cree during these migration periods. The decline in eelgrass and geese threatens culturally significant hunting activities of the First Nation Cree communities of Chisasibi, Wemindji, Eastmain, and Waskaganish. Multiple hypotheses exist for the eelgrass decline but no causes have been directly linked to the loss of eelgrass. As part of a larger coastal habitat monitoring program in James Bay focused on investigating the decline of eelgrass and potential threats and stressors, we developed novel eelgrass monitoring methods suited to the large spatial area and subarctic conditions as well as the eelgrass health index, an index for assessing eelgrass health status. This study assessed video monitoring as a potential methodology for monitoring eelgrass. Video monitoring and conventional observations were conducted side by side in the Great Bay Estuary in Maine and New Hampshire and compared. Observations for three eelgrass parameters, percent cover, shoot density, and plant height, were made during July and August 2019. Validation for each eelgrass parameter using conventional methods demonstrated that video monitoring results were consistent with results from conventional monitoring. Each of the parameters observed using both methods demonstrated a significant positive linear relationship (p \u3c 0.0001) with a moderate to strong goodness of fit. Cover and biomass data collected from this study and previous SeagrassNet monitoring surveys in the region were also used to develop a model to predict eelgrass biomass from percent cover. A simple linear regression using square root transformed biomass was selected as the best model to estimate biomass from cover. Based on the results, the novel video monitoring methodology is found to be a reliable alternative to conventional monitoring methods, which can improve the ability to collect comprehensive data during field monitoring under certain conditions. The validated video monitoring methods were then applied to assess the current health of James Bay eelgrass beds. Monitoring of eelgrass percent cover, shoot density, plant height, and biomass was conducted from June to September in 2017 and 2018. Eelgrass cover, density, and height were averaged using the geometric mean equation and reference values to calculate the eelgrass health index (EHI)—a novel tool for assessing eelgrass health status. The eelgrass health index was validated using two methods: 1) biomass observations from James Bay and from five long-term SeagrassNet eelgrass monitoring sites in the United States, and 2) a survey of experiential knowledge. We found that ratings from the new EHI are consistent with accepted metrics and can be used across North America, and with further testing, the EHI could potentially be applied to eelgrass beds throughout the northern hemisphere. We found that eelgrass is impaired throughout eastern James Bay. Contemporary EHI ratings were compared to historic eelgrass data using a model to predict eelgrass cover from biomass. We found that in comparison to EHI ratings calculated from the historic data, contemporary eelgrass health has declined at two sites in northern Chisasibi, Attikuan and Tees Bay and persisted in similar conditions to the historic environment at Kakassituk. You may view the thesis presentation accompanying slides here: https://scholars.unh.edu/thesis/141