An underwater vision compendium for the optometrist

A comprehensive compendium was assembled to aid the optometrist in understanding vision underwater and the unique visual needs of the SCUBA diver. Most every aspect of vision is altered underwater and a description of perceptual, optical, and physiolotical alterations is provided in the text. Partial adaptation to visual distortions gradually occurs as a function of time underwater, but adaptation can be accelerated with selected eye-hand activities. Methods of restoring the air-cornea interface are evaluated, and although the dive mask results in compromised visual function, it is still the most practical and cost effective means of restoring the refractive power of the eye. Based on personal experience and previous research, the authors suggest priorities for the novice diver selecting a dive mask. The ametropic diver is faced with choosing from four popularly available methods in selecting an underwater correction. Advantages and limitations of each method are cited. Lens bonded to the dive mask is the most versatile system but ultimate choice is dependent upon the diver\u27s specific, individual needs. In an appendix the authors explore a theoretical lens system that compensates for magnification created by the air-water interface of the facemask

Learning to Interpret Fluid Type Phenomena via Images

Learning to interpret fluid-type phenomena via images is a long-standing challenging problem in computer vision. The problem becomes even more challenging when the fluid medium is highly dynamic and refractive due to its transparent nature. Here, we consider imaging through such refractive fluid media like water and air. For water, we design novel supervised learning-based algorithms to recover its 3D surface as well as the highly distorted underground patterns. For air, we design a state-of-the-art unsupervised learning algorithm to predict the distortion-free image given a short sequence of turbulent images. Specifically, we design a deep neural network that estimates the depth and normal maps of a fluid surface by analyzing the refractive distortion of a reference background pattern. Regarding the recovery of severely downgraded underwater images due to the refractive distortions caused by water surface fluctuations, we present the distortion-guided network (DG-Net) for restoring distortion-free underwater images. The key idea is to use a distortion map to guide network training. The distortion map models the pixel displacement caused by water refraction. Furthermore, we present a novel unsupervised network to recover the latent distortion-free image. The key idea is to model non-rigid distortions as deformable grids. Our network consists of a grid deformer that estimates the distortion field and an image generator that outputs the distortion-free image. By leveraging the positional encoding operator, we can simplify the network structure while maintaining fine spatial details in the recovered images. We also develop a combinational deep neural network that can simultaneously perform recovery of the latent distortion-free image as well as 3D reconstruction of the transparent and dynamic fluid surface. Through extensive experiments on simulated and real captured fluid images, we demonstrate that our proposed deep neural networks outperform the current state-of-the-art on solving specific tasks

exPIERience

The name of this project is called “exPIERience” and the technological field of focus is virtual reality. We will be working on creating a virtual reality experience using the Oculus Rift for the Center of Coastal Marine Sciences (CCMS). The purpose of this system is to enable people to experience diving at the Cal Poly Pier even during nonoptimal diving conditions which occur frequently. CCMS hopes to attract further interest and possible momentum in future outreach such as a “Live Dive” program, where live videos of divers under the pier can be streamed. A 360° video from the diver’s perspective will be recorded during the diver’s journey through the water. These captured images will be recreated into a 3D space that will simulate an experience as if the user of the headset is the actual diver. We will need to build a camera system that will properly record an entire 360° view of the space that the diver experiences first hand. In addition to this system, an easy-to use control system must be built for proper navigation throughout the 3D space. We hope to deliver a design that will enable users of all expertise to operate the device and have the same user experience

New 3-d video methods reveal novel territorial drift-feeding behaviors that help explain environmental correlates of Chena River chinook salmon productivity

Thesis (Ph.D.) University of Alaska Fairbanks, 2014.Chinook salmon (Oncorhynchus tshawytscha) are critical to subsistence and commerce in the Yukon River basin, but several recent years of low abundance have forced devastating fishery closures and raised urgent questions about causes of the decline. The Chena River subpopulation in interior Alaska has experienced a decline similar to that of the broader population. To evaluate possible factors affecting Chena River Chinook salmon productivity, I analyzed both population data and the behavior of individual fish during the summer they spend as fry drift feeding in the river. Using a stereo pair of high definition video cameras, I recorded the fine-scale behavior of schools of juvenile Chinook salmon associated with woody debris along the margins of the Chena River. I developed a software program called VidSync that recorded 3-D measurements with sub-millimeter accuracy and provided a streamlined workflow for the measurement of several thousand 3-D points of behavioral data (Chapter 1). Juvenile Chinook salmon spent 91% of their foraging attempts investigating and rejecting debris rather than capturing prey, which affects their energy intake rate and makes foraging attempt rate an unreliable indicator of foraging success (Chapter 2). Even though Chinook salmon were schooling, some were highly territorial within their 3-D school configurations, and many others maintained exclusive space-use behaviors consistent with the population regulatory effects of territoriality observed in other salmonids (Chapter 3). Finally, a twenty-year population time series from the Chena River and neighboring Salcha River contained evidence for negative density dependence and a strong negative effect of sustained high summer stream discharge on productivity (Chapter 4). The observed territoriality may explain the population's density dependence, and the effect of debris on foraging efficiency represents one of many potential mechanisms behind the negative effect of high stream discharge. In combination, these findings contribute to a statistically and mechanistically plausible explanation for the recent decline in Chena River Chinook salmon. If they are, in fact, major causes of the decline (other causes cannot be ruled out), then we can be tentatively hopeful that the population may be experiencing a natural lull in abundance from which a recovery is possible.General Introduction -- Chapter 1: Measuring fish and their habitats: Versatile 2-D and 3-D video techniques with user-friendly software -- Chapter 2: Mechanisms of drift-feeding behavior in juvenile Chinook salmon and the role of inedible debris in a clear-water Alaskan Stream -- Chapter 3: Territoriality within schools: dynamic competition of drift-feeding juvenile Chinook salmon in 3-dimensional space -- Chapter 4: Low productivity of Chinook salmon strongly correlates with high summer stream discharge in two Alaskan rivers in the Yukon drainage

Plenoptic Signal Processing for Robust Vision in Field Robotics

This thesis proposes the use of plenoptic cameras for improving the robustness and simplicity of machine vision in field robotics applications. Dust, rain, fog, snow, murky water and insufficient light can cause even the most sophisticated vision systems to fail. Plenoptic cameras offer an appealing alternative to conventional imagery by gathering significantly more light over a wider depth of field, and capturing a rich 4D light field structure that encodes textural and geometric information. The key contributions of this work lie in exploring the properties of plenoptic signals and developing algorithms for exploiting them. It lays the groundwork for the deployment of plenoptic cameras in field robotics by establishing a decoding, calibration and rectification scheme appropriate to compact, lenslet-based devices. Next, the frequency-domain shape of plenoptic signals is elaborated and exploited by constructing a filter which focuses over a wide depth of field rather than at a single depth. This filter is shown to reject noise, improving contrast in low light and through attenuating media, while mitigating occluders such as snow, rain and underwater particulate matter. Next, a closed-form generalization of optical flow is presented which directly estimates camera motion from first-order derivatives. An elegant adaptation of this "plenoptic flow" to lenslet-based imagery is demonstrated, as well as a simple, additive method for rendering novel views. Finally, the isolation of dynamic elements from a static background is considered, a task complicated by the non-uniform apparent motion caused by a mobile camera. Two elegant closed-form solutions are presented dealing with monocular time-series and light field image pairs. This work emphasizes non-iterative, noise-tolerant, closed-form, linear methods with predictable and constant runtimes, making them suitable for real-time embedded implementation in field robotics applications

Plenoptic Signal Processing for Robust Vision in Field Robotics

This thesis proposes the use of plenoptic cameras for improving the robustness and simplicity of machine vision in field robotics applications. Dust, rain, fog, snow, murky water and insufficient light can cause even the most sophisticated vision systems to fail. Plenoptic cameras offer an appealing alternative to conventional imagery by gathering significantly more light over a wider depth of field, and capturing a rich 4D light field structure that encodes textural and geometric information. The key contributions of this work lie in exploring the properties of plenoptic signals and developing algorithms for exploiting them. It lays the groundwork for the deployment of plenoptic cameras in field robotics by establishing a decoding, calibration and rectification scheme appropriate to compact, lenslet-based devices. Next, the frequency-domain shape of plenoptic signals is elaborated and exploited by constructing a filter which focuses over a wide depth of field rather than at a single depth. This filter is shown to reject noise, improving contrast in low light and through attenuating media, while mitigating occluders such as snow, rain and underwater particulate matter. Next, a closed-form generalization of optical flow is presented which directly estimates camera motion from first-order derivatives. An elegant adaptation of this "plenoptic flow" to lenslet-based imagery is demonstrated, as well as a simple, additive method for rendering novel views. Finally, the isolation of dynamic elements from a static background is considered, a task complicated by the non-uniform apparent motion caused by a mobile camera. Two elegant closed-form solutions are presented dealing with monocular time-series and light field image pairs. This work emphasizes non-iterative, noise-tolerant, closed-form, linear methods with predictable and constant runtimes, making them suitable for real-time embedded implementation in field robotics applications

Ocean Literacy for All: A Tool Kit

This publication is made of two parts. The first part presents the history of oceanliteracy, and describes its framework made of 7 essential principles, and connectsthem to international ocean science programs that contributes to enhancing oceanknowledge and observations. Moreover, marine scientists and educators wereinterviewed to share their professional experiences on ocean literacy as well astheir views on its future. The last chapter of part 1 describes the existing challengesto marine education, as well as the path for the development of successful oceanliteracy activities in the context of the 2030 Agenda. One of the most importantfactors identified is related to the creation of multi-sector partnerships amongthe education, government, and private sector that have jointly built ocean literacyprograms for all formal educational levels from the primary school to the universitylevel as well as for non-formal learners. Worldwide examples of such programs arepresented.The second part, after introducing the methodological approach based on themulti-perspective framework for ESD developed by UNESCO, presents 14 activitiesthat could provide tested examples and support for the implementation of marineeducation initiatives. The aim is not to provide a one size-fits-all ready to usecollection, but rather to offer support and examples of what could be then adaptedfor different geographical and cultural contexts. The resources are designed to berelevant for all learners of all ages worldwide and to find their application in manylearning settings, while in their concrete implementation they will, naturally, haveto be adapted to the national or local context

High Performance Optical Computed Tomography for Accurate Three-Dimensional Radiation Dosimetry

Optical computed tomography (CT) imaging of radiochromic gel dosimeters is a method for truly three-dimensional radiation dosimetry. Although optical CT dosimetry is not widely used currently due to previous concerns with speed and accuracy, the complexity of modern radiotherapy is increasing the need for a true 3D dosimeter. This thesis reports technical improvements that bring the performance of optical CT to a clinically useful level. New scanner designs and improved scanning and reconstruction techniques are described. First, we designed and implemented a new light source for a cone-beam optical CT system which reduced the scatter to primary contribution in CT projection images of gel dosimeters from approximately 25% to approximately 4%. This design, which has been commercially implemented, enables accurate and fast dosimetry. Second, we designed and constructed a new, single-ray, single-detector parallel-beam optical CT scanner. This system was able to very accurately image both absorbing and scattering objects in large volumes (15 cm diameter), agreeing within ∼1% with independent measurements. It has become a reference standard for evaluation of optical CT geometries and dosimeter formulations. Third, we implemented and characterized an iterative reconstruction algorithm for optical CT imaging of gel dosimeters. This improved image quality in optical CT by suppressing the effects of noise and artifacts by a factor of up to 5. Fourth, we applied a fiducial-based ray path measurement scheme, combined with an iterative reconstruction algorithm, to enable optical CT reconstruction in the case of refractive index mismatch between different media in the scanner’s imaged volume. This improved the practicality of optical CT, as time-consuming mixing of liquids can be avoided. Finally, we applied the new laser scanner to the difficult dosimetry task of small-field measurement. We were able to obtain beam profiles and depth dose curves for 4 fields (3x3 cm2 and below) using one 15 cm diameter dosimeter, within 2 hours. Our gel dosimetry depth-dose curves agreed within ∼1.5% with Monte Carlo simulations. In conclusion, the developments reported here have brought optical CT dosimetry to a clinically useful level. Our techniques will be used to assist future research in gel dosimetry and radiotherapy treatment techniques