Fisheye Views Research Articles

Fisheye Night Sky Imager: A Calibrated Tool to Measure Night Sky Brightness

The Night Skies Team of the U.S. National Park Service (NPS) has developed a new camera system equipped with a fisheye lens to measure night sky brightness. This NPS Fisheye Night Sky Imager comprises a back-illuminated Sony IMX455 CMOS sensor housed in the ZWO ASI6200MM camera, a Johnson V filter, and a Sigma 8 mm F3.5 fisheye lens. All of the components are commercially available. The fisheye lens allows us to capture the entire sky in a single frame. The wide-angle view also introduces calibration challenges. To address this, we have customized tools and devised innovative methods for calibrating the system, including flat-field correction, pixel scale determination, and field of view characterization. Additionally, we use standard stars for precise positional and photometric calibration. Furthermore, we create an open-source Python pipeline to process these fisheye images and leverage Git and GitHub for source code version control and distribution. The resulting images provide a positionally and brightness-calibrated fisheye view of the night sky, with a photometric calibration uncertainty of 0.12 mag. When comparing our Fisheye Night Sky Imager measurements to images taken with other calibrated systems, we reliably achieve consistent results under both dark and bright skies. Our Fisheye Night Sky Imager not only enables rapid assessment of sky quality but also supports the feasibility of establishing permanent monitoring locations. Recognizing that the natural dark sky is a critical element for natural, cultural, educational, and visitor experiences, this new camera system enhances our ability to assess resource conditions and fulfill the NPS mission of conserving resources unimpaired for the enjoyment of this and future generations.

Evaluating Trinocular Camera Configurations and Fisheye View for Enhanced Feature-based Visual Aerial Odometry

Evaluating Trinocular Camera Configurations and Fisheye View for Enhanced Feature-based Visual Aerial Odometry

A Fish Eye View: Retinal Morphogenesis from Optic Cup to Neuronal Lamination.

The neural retina, at the back of the eye, is a fascinating system to use to discover how cells form tissues in the context of the developing nervous system. The retina is the tissue responsible for perception and transmission of visual information from the environment. It consists of five types of neurons and one type of glia cells that are arranged in a highly organized, layered structure to assure visual information flow. To reach this highly ordered arrangement, intricate morphogenic movements are occurring at the cell and tissue levels. I here discuss recent advances made to understand retinal development, from optic cup formation to neuronal layering. It becomes clear that these complex morphogenetic processes must be studied by taking the cellular as well as the tissue-wide aspects into account. The loop has to be closed between exploring how cell behavior influences tissue development and how the surrounding tissue itself influences single cells. Furthermore, it was recently revealed that the retina is a great system to study neuronal migration phenomena, and more is yet to be discovered in this aspect. Constantly developing imaging and image analysis toolboxes as well as the use of machine learning and synthetic biology make the retina the perfect system to explore more of its exciting neurodevelopmental biology.

Mitigating Bias in Algorithmic Systems—A Fish-eye View

Mitigating bias in algorithmic systems is a critical issue drawing attention across communities within the information and computer sciences. Given the complexity of the problem and the involvement of multiple stakeholders—including developers, end users, and third-parties—there is a need to understand the landscape of the sources of bias, and the solutions being proposed to address them, from a broad, cross-domain perspective. This survey provides a “fish-eye view,” examining approaches across four areas of research. The literature describes three steps toward a comprehensive treatment—bias detection, fairness management, and explainability management—and underscores the need to work from within the system as well as from the perspective of stakeholders in the broader context.

GNSS NLOS Signal Classification Based on Machine Learning and Pseudorange Residual Check.

Global navigation satellite system (GNSS) positioning has recently garnered attention for autonomous driving, machine control, and construction sites. With the development of low-cost multi-GNSS receivers and the advent of new types of GNSS, such as Japan’s Quasi-Zenith Satellite System, the potential of GNSS positioning has increased. New types of GNSS directly increase the number of line-of-sight (LOS) signals in dense urban areas and improve positioning accuracy. However, GNSS receivers can observe both LOS and non-line-of-sight (NLOS) signals in dense urban areas, and more NLOS signals are observed under static conditions than under dynamic conditions. The classification of LOS and NLOS signals is important, and various methods have been proposed, such as C/N0, using three-dimensional maps, fish-eye view, and GNSS/inertial navigation system integration. Multipath detection based on machine learning has also been reported in recent years. In this study, we propose a method for detecting NLOS signals using a support vector machine (SVM) classifier modeled with unique features that are calculated by receiver independent exchange format-based information and GNSS pseudorange residual check. We found that using both the SVM classifier and GNSS pseudorange residual check effectively reduced the error due to NLOS signals. Several static tests were conducted near high-rise buildings that are likely to receive some NLOS signals in downtown Tokyo. For all static tests, the percentage of positioning errors within 10 m in the horizontal positioning error was improved by >80% by detecting and eliminating satellites receiving NLOS signals.

Mitigating Bias in Algorithmic Systems - A Fish-Eye View

Mitigating Bias in Algorithmic Systems - A Fish-Eye View

Mitigating Bias in Algorithmic Systems - A Fish-Eye View

Mitigating bias in algorithmic systems is a critical issue drawing attention across communities within the information and computer sciences. Given the complexity of the problem and the involvement of multiple stakeholders -- including developers, end-users, and third parties -- there is a need to understand the landscape of the sources of bias, and the solutions being proposed to address them, from a broad, cross-domain perspective. This survey provides a "fish-eye view," examining approaches across four areas of research. The literature describes three steps toward a comprehensive treatment -- bias detection, fairness management and explainability management -- and underscores the need to work from within the system as well as from the perspective of stakeholders in the broader context.

Mitigating Bias in Algorithmic Systems - A Fish-Eye View

Mitigating Bias in Algorithmic Systems - A Fish-Eye View

Radial Distortion of the Arthroscopic Transtibial Portal: A 2-Dimensional in Vitro Model

Purpose: To make the positioning of the anterior cruciate ligament (ACL) transplants as precise as possible, it is necessary to better visualize the foot-print. Identifying anatomic sites is complicated by image distortion inherent in arthroscopy. The standard “Outside-In” ACL reconstruction technique involves drilling a tunnel, i.e. an aperture on the surface of the tibia for the purpose of placing the bone-tendon-bone transplant. This operative technique opens another approach to the inside of the knee, through the tibial plateau (Transtibial-TT). The aim of this manuscript is to assess optimal arthroscopic visibility by calculating radial distortion, arthroscopy insertion positions and different knee bending angles. Methods: We used a standard dot array calibration pattern, an arthroscopic imaging system and Sawbones knee models. The standard deviation and relative standard deviation of distances obtained at distortion of the images were calculated. Results: All captured imagines have shown the effect of distortion so called fish-eye view, i.e. the imagines at periphery were more curved and compressed. Conclusion: The least distorted arthroscopic image of the femoral ACL footprint can be obtained when using the TT portal and by bending the knee between 90° and 130° with a 30° arthroscope. Also, the best visualization is performed by drilling the tibia under the angle 0° in the sagittal plane and 23° in the coronal plane in comparison to the tibial surface.

Phobalysin: Fisheye View of Membrane Perforation, Repair, Chemotaxis and Adhesion.

Phobalysin P (PhlyP, for photobacterial lysin encoded on a plasmid) is a recently described small β-pore forming toxin of Photobacterium damselae subsp. damselae (Pdd). This organism, belonging to the family of Vibrionaceae, is an emerging pathogen of fish and various marine animals, which occasionally causes life-threatening soft tissue infections and septicemia in humans. By using genetically modified Pdd strains, PhlyP was found to be an important virulence factor. More recently, in vitro studies with purified PhlyP elucidated some basic consequences of pore formation. Being the first bacterial small β-pore forming toxin shown to trigger calcium-influx dependent membrane repair, PhlyP has advanced to a revealing model toxin to study this important cellular function. Further, results from co-culture experiments employing various Pdd strains and epithelial cells together with data on other bacterial toxins indicate that limited membrane damage may generally enhance the association of bacteria with target cells. Thereby, remodeling of plasma membrane and cytoskeleton during membrane repair could be involved. In addition, a chemotaxis-dependent attack-and track mechanism influenced by environmental factors like salinity may contribute to PhlyP-dependent association of Pdd with cells. Obviously, a synoptic approach is required to capture the regulatory links governing the interaction of Pdd with target cells. The characterization of Pdd’s secretome may hold additional clues because it may lead to the identification of proteases activating PhlyP’s pro-form. Current findings on PhlyP support the notion that pore forming toxins are not just killer proteins but serve bacteria to fulfill more subtle functions, like accessing their host.

A fish eye view of the mirror test.

Reactions to a recent study suggesting that cleaner wrasse can pass the mirror self-recognition test (Kohda et al. in PLOS Biology, 17(2), e3000021, 2019) reveal more about scientists' biases than about self-awareness. Scientists should base conclusions about species' abilities based on the corpus of data on that species rather than on a single test or preconceived expectations based on phylogeny alone.

Structure-aware Fisheye Views for Efficient Large Graph Exploration.

Traditional fisheye views for exploring large graphs introduce substantial distortions that often lead to a decreased readability of paths and other interesting structures. To overcome these problems, we propose a framework for structure-aware fisheye views. Using edge orientations as constraints for graph layout optimization allows us not only to reduce spatial and temporal distortions during fisheye zooms, but also to improve the readability of the graph structure. Furthermore, the framework enables us to optimize fisheye lenses towards specific tasks and design a family of new lenses: polyfocal, cluster, and path lenses. A GPU implementation lets us process large graphs with up to 15,000 nodes at interactive rates. A comprehensive evaluation, a user study, and two case studies demonstrate that our structure-aware fisheye views improve layout readability and user performance.

First Study on the Occurrence Frequency of Equatorial Plasma Bubbles over West Africa Using an All‐Sky Airglow Imager and GNSS Receivers

AbstractThis is the first paper that reports the occurrence frequency of equatorial plasma bubbles and their dependences of local time, season, and geomagnetic activity based on airglow imaging observations at West Africa. The all‐sky imager, situated in Abuja (Geographic: 8.99°N, 7.38°E; Geomagnetic: 1.60°S), has a 180° fisheye view covering almost the entire airspace of Nigeria. Plasma bubbles are observed for 70 nights of the 147 clear‐sky nights from 9 June 2015 to 31 January 2017. Differences between nighttime and daytime ROTIs were also computed as a proxy of plasma bubbles using Global Navigation Satellite Systems (GNSS) receivers within the coverage of the all‐sky imager. Most plasma bubble occurrences are found during equinoxes and least occurrences during solstices. The occurrence rate of plasma bubbles was highest around local midnight and lower for hours farther away. Most of the postmidnight plasma bubbles were observed around the months of December to March, a period that coincides with the harmattan period in Nigeria. The on/off status of plasma bubble in airglow and GNSS observations were in agreement for 67.2% of the total 768 h, while we suggest several reasons responsible for the remaining 32.8% when the airglow and GNSS bubble status are inconsistent. A majority of the plasma bubbles were observed under relatively quiet geomagnetic conditions (Dst ≥ −40 and Kp ≤ 3), but there was no significant pattern observed in the occurrence rate of plasma bubbles as a function of geomagnetic activity. We suggest that geomagnetic activities could have either suppressed or promoted the occurrence of plasma bubbles.

Sky View Factors from Synthetic Fisheye Photos for Thermal Comfort Routing—A Case Study in Phoenix, Arizona

The Sky View Factor (SVF) is a dimension-reduced representation of urban form and one of the major variables in radiation models that estimate outdoor thermal comfort. Common ways of retrieving SVFs in urban environments include capturing fisheye photographs or creating a digital 3D city or elevation model of the environment. Such techniques have previously been limited due to a lack of imagery or lack of full scale detailed models of urban areas. We developed a web based tool that automatically generates synthetic hemispherical fisheye views from Google Earth at arbitrary spatial resolution and calculates the corresponding SVFs through equiangular projection. SVF results were validated using Google Maps Street View and compared to results from other SVF calculation tools. We generated 5-meter resolution SVF maps for two neighborhoods in Phoenix, Arizona to illustrate fine-scale variations of intra-urban horizon limitations due to urban form and vegetation. To demonstrate the utility of our synthetic fisheye approach for heat stress applications, we automated a radiation model to generate outdoor thermal comfort maps for Arizona State University’s Tempe campus for a hot summer day using synthetic fisheye photos and on-site meteorological data. Model output was tested against mobile transect measurements of the six-directional radiant flux density. Based on the thermal comfort maps, we implemented a pedestrian routing algorithm that is optimized for distance and thermal comfort preferences. Our synthetic fisheye approach can help planners assess urban design and tree planting strategies to maximize thermal comfort outcomes and can support heat hazard mitigation in urban areas.

EgoCap

Marker-based and marker-less optical skeletal motion-capture methods use an outside-in arrangement of cameras placed around a scene, with viewpoints converging on the center. They often create discomfort with marker suits, and their recording volume is severely restricted and often constrained to indoor scenes with controlled backgrounds. Alternative suit-based systems use several inertial measurement units or an exoskeleton to capture motion with an inside-in setup, i.e. without external sensors. This makes capture independent of a confined volume, but requires substantial, often constraining, and hard to set up body instrumentation. Therefore, we propose a new method for real-time, marker-less, and egocentric motion capture: estimating the full-body skeleton pose from a lightweight stereo pair of fisheye cameras attached to a helmet or virtual reality headset - an optical inside-in method, so to speak. This allows full-body motion capture in general indoor and outdoor scenes, including crowded scenes with many people nearby, which enables reconstruction in larger-scale activities. Our approach combines the strength of a new generative pose estimation framework for fisheye views with a ConvNet-based body-part detector trained on a large new dataset. It is particularly useful in virtual reality to freely roam and interact, while seeing the fully motion-captured virtual body.

Data Flow Diagrams of an Electronic Medical Record System in Mansoura Hospital

This paper develops an Electronic Medical Record System in the Neurosurgical Unit of Mansoura General Hospital using Data Flow Diagrams. Data Flow Diagrams are the first step to design the system blueprint as they represent users requirements. The paper creates a context-aware fisheye view as it is more successfully communicate the information contained in a set of Data Flow Diagrams (DFD) than a traditional context-free presentation. A case study and experimental results show that our context-aware fisheye DFD's are well suited for application in developing Electronic Medical Record System. This makes the expert system more reliable and faster response

An interactive visualization approach to the overview of geoscience data

Geoscience observation data refer to the datasets consisting of time series of multiple parameters generated from the sensors at fixed locations. Although a few works have attempted to visualize such data, none of them views these data as a specific type and attempts to show the overview in all the space, time and attribute aspects. It is important for domain experts to select the subsets of interest from huge amounts of observation data according to the high level patterns shown in the overview. We present a novel approach to visualize geoscience observation data in a compact radial view. Our solution consists of three visual elements. A map showing the spatial aspect is in the center of the visualization, while temporal and attribute aspects are seamlessly combined with the spatial information. Our approach is equipped with interactive mechanisms for highlighting the selected features, adjusting the display range, as well as interactively generating a fisheye view. We demonstrate the usability of our approach with three case studies of different domains. Eye tracking records and user feedbacks obtained in a small experiment also prove the effectiveness of our approach.

A fish-eye view of riverine hydropower systems: the current understanding of the biological response to turbine passage

One-way connectivity maintained by fish passing through hydropower turbines in fragmented rivers can be important to population dynamics, but can also introduce a new and significant source of mortality. Sources of mortality during turbine passage can come from several sources including blade strike, shear forces, cavitation, or pressure decreases and parsing the contributions of these individual forces is important for advancing and deploying turbines that minimize these impacts to fishes. We used a national hydropower database and conducted a systematic review of the literature to accomplish three goals: (1) report on the spatial distribution of turbine types and generation capacities in the USA, (2) determine fish mortality rates among turbine types and fish species and (3) examine relationships between physical forces similar to those encountered during fish turbine passage and fish injury and mortality. We found that while Francis turbines generate 56 % of all US hydropower and have the highest associated fish mortality of any turbine type, these turbines are proportionally understudied compared to less-common and less injury-associated Kaplan turbines, particularly in the Pacific Northwest. While juvenile salmonid species in actual or simulated Kaplan turbine conditions were the most commonly studied, the highest mortality rates were reported from percid fishes passing through Francis turbines. Future studies should focus on understanding which species are most at-risk to turbine passage injury and mortality and, subsequently, increasing the diversity of taxonomy and turbine types in evaluations of turbine injury and mortality.

A fish-eye view on the new Arctic lightscape

Abstract A gigantic light experiment is taking place in the Arctic. Climate change has led to substantial reductions in sea ice extent and thickness in the Arctic Ocean. Sea ice, particularly when snow covered, acts as a lid hindering light to reach the waters underneath. Less ice will therefore mean more light entering the water column, with profound effects on pelagic and benthic ecosystems. Responses through primary production are so far well acknowledged. Here we argue that there is a need to broaden the view to include light-driven effects on fish, as they depend on light to locate prey. We used the Norwegian Earth System Model estimates of past and future sea ice area and thickness in the Arctic and applied attenuation coefficients for ice and snow to estimate light intensity. The results show a dramatic increase in the amount of light predicted to reach the future Arctic Ocean. We combined this insight with mechanistic understanding of how light modulates visual prey-detection and predict that fish will forage more efficiently as sea ice diminishes and that their populations will expand to higher latitudes, at least seasonally. Poleward shifts of boreal fish species have been predicted by many and to some extent observed, but a changing light environment has so far not been considered a driver. Expanding distributions and greater visual predation may restructure ecological relationships throughout the Arctic foodweb and lead to regime shifts. Research efforts should focus on the dynamics of how less sea ice will affect the feeding ecology and habitat usage of fish, particularly the northern limits of distributions. Mechanistic approaches to these topics offer insights beyond statistical correlations and extrapolations, and will help us understand how changing biophysical dynamics in the Arctic influence complex processes including production, predator–prey interactions, trait-evolution, and fisheries.

The Effect of Dynamic (Fisheye) Feature in a Speedometer on Driver's Speed Reading Performance

The objectives of this study were to investigate the effects of different speedometer features, especially dynamic speedometer using fisheye view for speed readout on driver's current speed-reading performance and preference. Two experiments were conducted. In the first experiment, shape of speedometer (full-circle and half-circle), resolution of speed readout (5s and 10s mph), and font size layout (fixed, stepped, and gradually increasing) were manipulated using static prototypes. Twenty participants’ response time and answer duration for reading current speed were collected as performance measures, along with subjective preferences. Based on findings in the first experiment, Java-based speedometer prototypes were developed and integrated with a driving simulator for the second experiment. Eight different speedometer features consisted of shapes of speedometer (half-circle and full-circle), resolutions of speed readout (10s and 20s mph), and dynamics of font size layout (static [fixed] and dynamic font size changes [fisheye view]) were manipulated in the interactive speedometer prototypes. Sixteen participants’ response time, answer duration, eye dwell time on speedometer, and subjective preferences were collected for the measurement. The results demonstrated similar utility of both speedometer shapes (full and half circle), optimal level of speed readout resolution, and potential utility of dynamic speedometer feature. The results of the study may provide a basis for future speedometer design in a flexible/configurable instrument cluster to improve driving performance and safety.