834 resultados para CAMERAS


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Transmission electron microscopy has provided most of what is known about the ultrastructural organization of tissues, cells, and organelles. Due to tremendous advances in crystallography and magnetic resonance imaging, almost any protein can now be modeled at atomic resolution. To fully understand the workings of biological "nanomachines" it is necessary to obtain images of intact macromolecular assemblies in situ. Although the resolution power of electron microscopes is on the atomic scale, in biological samples artifacts introduced by aldehyde fixation, dehydration and staining, but also section thickness reduces it to some nanometers. Cryofixation by high pressure freezing circumvents many of the artifacts since it allows vitrifying biological samples of about 200 mum in thickness and immobilizes complex macromolecular assemblies in their native state in situ. To exploit the perfect structural preservation of frozen hydrated sections, sophisticated instruments are needed, e.g., high voltage electron microscopes equipped with precise goniometers that work at low temperature and digital cameras of high sensitivity and pixel number. With them, it is possible to generate high resolution tomograms, i.e., 3D views of subcellular structures. This review describes theory and applications of the high pressure cryofixation methodology and compares its results with those of conventional procedures. Moreover, recent findings will be discussed showing that molecular models of proteins can be fitted into depicted organellar ultrastructure of images of frozen hydrated sections. High pressure freezing of tissue is the base which may lead to precise models of macromolecular assemblies in situ, and thus to a better understanding of the function of complex cellular structures.

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Magmatic volatiles play a crucial role in volcanism, from magma production at depth to generation of seismic phenomena to control of eruption style. Accordingly, many models of volcano dynamics rely heavily on behavior of such volatiles. Yet measurements of emission rates of volcanic gases have historically been limited, which has restricted model verification to processes on the order of days or longer. UV cameras are a recent advancement in the field of remote sensing of volcanic SO2 emissions. They offer enhanced temporal and spatial resolution over previous measurement techniques, but need development before they can be widely adopted and achieve the promise of integration with other geophysical datasets. Large datasets require a means by which to quickly and efficiently use imagery to calculate emission rates. We present a suite of programs designed to semi-automatically determine emission rates of SO2 from series of UV images. Extraction of high temporal resolution SO2 emission rates via this software facilitates comparison of gas data to geophysical data for the purposes of evaluating models of volcanic activity and has already proven useful at several volcanoes. Integrated UV camera and seismic measurements recorded in January 2009 at Fuego volcano, Guatemala, provide new insight into the system’s shallow conduit processes. High temporal resolution SO2 data reveal patterns of SO2 emission rate relative to explosions and seismic tremor that indicate tremor and degassing share a common source process. Progressive decreases in emission rate appear to represent inhibition of gas loss from magma as a result of rheological stiffening in the upper conduit. Measurements of emission rate from two closely-spaced vents, made possible by the high spatial resolution of the camera, help constrain this model. UV camera measurements at Kilauea volcano, Hawaii, in May of 2010 captured two occurrences of lava filling and draining within the summit vent. Accompanying high lava stands were diminished SO2 emission rates, decreased seismic and infrasonic tremor, minor deflation, and slowed lava lake surface velocity. Incorporation of UV camera data into the multi-parameter dataset gives credence to the likelihood of shallow gas accumulation as the cause of such events.

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Obesity is becoming an epidemic phenomenon in most developed countries. The fundamental cause of obesity and overweight is an energy imbalance between calories consumed and calories expended. It is essential to monitor everyday food intake for obesity prevention and management. Existing dietary assessment methods usually require manually recording and recall of food types and portions. Accuracy of the results largely relies on many uncertain factors such as user's memory, food knowledge, and portion estimations. As a result, the accuracy is often compromised. Accurate and convenient dietary assessment methods are still blank and needed in both population and research societies. In this thesis, an automatic food intake assessment method using cameras, inertial measurement units (IMUs) on smart phones was developed to help people foster a healthy life style. With this method, users use their smart phones before and after a meal to capture images or videos around the meal. The smart phone will recognize food items and calculate the volume of the food consumed and provide the results to users. The technical objective is to explore the feasibility of image based food recognition and image based volume estimation. This thesis comprises five publications that address four specific goals of this work: (1) to develop a prototype system with existing methods to review the literature methods, find their drawbacks and explore the feasibility to develop novel methods; (2) based on the prototype system, to investigate new food classification methods to improve the recognition accuracy to a field application level; (3) to design indexing methods for large-scale image database to facilitate the development of new food image recognition and retrieval algorithms; (4) to develop novel convenient and accurate food volume estimation methods using only smart phones with cameras and IMUs. A prototype system was implemented to review existing methods. Image feature detector and descriptor were developed and a nearest neighbor classifier were implemented to classify food items. A reedit card marker method was introduced for metric scale 3D reconstruction and volume calculation. To increase recognition accuracy, novel multi-view food recognition algorithms were developed to recognize regular shape food items. To further increase the accuracy and make the algorithm applicable to arbitrary food items, new food features, new classifiers were designed. The efficiency of the algorithm was increased by means of developing novel image indexing method in large-scale image database. Finally, the volume calculation was enhanced through reducing the marker and introducing IMUs. Sensor fusion technique to combine measurements from cameras and IMUs were explored to infer the metric scale of the 3D model as well as reduce noises from these sensors.

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This presentation provides an overview of the type of work that involves trying to resolve human/grizzly bear conflicts. Much of this work involves public education, cap-turing, handling, and monitoring grizzly bears, the use of Karelian Bear Dogs, and using new technology. Some of the new technology includes the use of remote cameras, an au-tomated bear trap, microchips, DNA, GPS radio collars, and an Electro-Optic/Infrared imagery system to locate grizzly bears.

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Vegetation phenology is an important indicator of climate change and climate variability and it is strongly connected to biospheric–atmospheric gas exchange. We aimed to evaluate the applicability of phenological information derived from digital imagery for the interpretation of CO2 exchange measurements. For the years 2005–2007 we analyzed seasonal phenological development of 2 temperate mixed forests using tower-based imagery from standard RGB cameras. Phenological information was jointly analyzed with gross primary productivity (GPP) derived from net ecosystem exchange data. Automated image analysis provided reliable information on vegetation developmental stages of beech and ash trees covering all seasons. A phenological index derived from image color values was strongly correlated with GPP, with a significant mean time lag of several days for ash trees and several weeks for beech trees in early summer (May to mid-July). Leaf emergence dates for the dominant tree species partly explained temporal behaviour of spring GPP but were also masked by local meteorological conditions. We conclude that digital cameras at flux measurement sites not only provide an objective measure of the physiological state of a forest canopy at high temporal and spatial resolutions, but also complement CO2 and water exchange measurements, improving our knowledge of ecosystem processes.

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Many applications, such as telepresence, virtual reality, and interactive walkthroughs, require a three-dimensional(3D)model of real-world environments. Methods, such as lightfields, geometric reconstruction and computer vision use cameras to acquire visual samples of the environment and construct a model. Unfortunately, obtaining models of real-world locations is a challenging task. In particular, important environments are often actively in use, containing moving objects, such as people entering and leaving the scene. The methods previously listed have difficulty in capturing the color and structure of the environment while in the presence of moving and temporary occluders. We describe a class of cameras called lag cameras. The main concept is to generalize a camera to take samples over space and time. Such a camera, can easily and interactively detect moving objects while continuously moving through the environment. Moreover, since both the lag camera and occluder are moving, the scene behind the occluder is captured by the lag camera even from viewpoints where the occluder lies in between the lag camera and the hidden scene. We demonstrate an implementation of a lag camera, complete with analysis and captured environments.

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Adding virtual objects to real environments plays an important role in todays computer graphics: Typical examples are virtual furniture in a real room and virtual characters in real movies. For a believable appearance, consistent lighting of the virtual objects is required. We present an augmented reality system that displays virtual objects with consistent illumination and shadows in the image of a simple webcam. We use two high dynamic range video cameras with fisheye lenses permanently recording the environment illumination. A sampling algorithm selects a few bright parts in one of the wide angle images and the corresponding points in the second camera image. The 3D position can then be calculated using epipolar geometry. Finally, the selected point lights are used in a multi pass algorithm to draw the virtual object with shadows. To validate our approach, we compare the appearance and shadows of the synthetic objects with real objects.

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Having to carry input devices can be inconvenient when interacting with wall-sized, high-resolution tiled displays. Such displays are typically driven by a cluster of computers. Running existing games on a cluster is non-trivial, and the performance attained using software solutions like Chromium is not good enough. This paper presents a touch-free, multi-user, humancomputer interface for wall-sized displays that enables completely device-free interaction. The interface is built using 16 cameras and a cluster of computers, and is integrated with the games Quake 3 Arena (Q3A) and Homeworld. The two games were parallelized using two different approaches in order to run on a 7x4 tile, 21 megapixel display wall with good performance. The touch-free interface enables interaction with a latency of 116 ms, where 81 ms are due to the camera hardware. The rendering performance of the games is compared to their sequential counterparts running on the display wall using Chromium. Parallel Q3A’s framerate is an order of magnitude higher compared to using Chromium. The parallel version of Homeworld performed on par with the sequential, which did not run at all using Chromium. Informal use of the touch-free interface indicates that it works better for controlling Q3A than Homeworld.

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This paper presents different application scenarios for which the registration of sub-sequence reconstructions or multi-camera reconstructions is essential for successful camera motion estimation and 3D reconstruction from video. The registration is achieved by merging unconnected feature point tracks between the reconstructions. One application is drift removal for sequential camera motion estimation of long sequences. The state-of-the-art in drift removal is to apply a RANSAC approach to find unconnected feature point tracks. In this paper an alternative spectral algorithm for pairwise matching of unconnected feature point tracks is used. It is then shown that the algorithms can be combined and applied to novel scenarios where independent camera motion estimations must be registered into a common global coordinate system. In the first scenario multiple moving cameras, which capture the same scene simultaneously, are registered. A second new scenario occurs in situations where the tracking of feature points during sequential camera motion estimation fails completely, e.g., due to large occluding objects in the foreground, and the unconnected tracks of the independent reconstructions must be merged. In the third scenario image sequences of the same scene, which are captured under different illuminations, are registered. Several experiments with challenging real video sequences demonstrate that the presented techniques work in practice.

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Dieser Beitrag beschreibt die Integration von laufzeitmessenden 3D Kamerasystemen in die Gabelzinkenspitzen eines Flurförderzeugs. Mit Hilfe der integrierten Kameras und deren ausgewerteter Aufnahmen wurde ein Assistenzsystem für die Handhabung von Ladungsträgern realisiert, das dem Fahrer des Flurförderzeugs Verfahrempfehlungen für die Optimierung der Relativposition zwischen Gabelzinken und Ladungsträger bzw. Lagerplatz ausgibt. Neben der Vorstellung der verwendeten Kamera-Hardware und der Integration am Fahrzeug wird auch der Ablauf der Bildverarbeitung beschrieben.

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When depicting both virtual and physical worlds, the viewer's impression of presence in these worlds is strongly linked to camera motion. Plausible and artist-controlled camera movement can substantially increase scene immersion. While physical camera motion exhibits subtle details of position, rotation, and acceleration, these details are often missing for virtual camera motion. In this work, we analyze camera movement using signal theory. Our system allows us to stylize a smooth user-defined virtual base camera motion by enriching it with plausible details. A key component of our system is a database of videos filmed by physical cameras. These videos are analyzed with a camera-motion estimation algorithm (structure-from-motion) and labeled manually with a specific style. By considering spectral properties of location, orientation and acceleration, our solution learns camera motion details. Consequently, an arbitrary virtual base motion, defined in any conventional animation package, can be automatically modified according to a user-selected style. In an animation package the camera motion base path is typically defined by the user via function curves. Another possibility is to obtain the camera path by using a mixed reality camera in motion capturing studio. As shown in our experiments, the resulting shots are still fully artist-controlled, but appear richer and more physically plausible.

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ContentsPoll: Ideal study abroad location?One-on-one: Samantha WeeseEditorial: Cameras in CampustownISU collides with CERN's discoveriesIowa Games takes new direction

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ContentsEagles finally SOARTeach-in addresses partnershipRelay for Life unites people of Story CountySoftball falls to LonghornsDo cameras curb traffic violations?Main Street Cultural District moves toward a new look

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Introduction: Photography through a microscope is virtually identical to that used with an astronomical telescope. For years, the 35mm camera was the choice for microphotography, but we live in a digital camera age now. We describe a custom homemade adapter that can be fit most of the cameras and microscopes. [See PDF for complete abstract]

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In this investigation, bromine-77 was produced with a medical cyclotron and imaged with gamma cameras. Br-77 emits a 240 kev photon with a half life of 56 hours. The C-Br bond is stronger than the C-I bond and bromine is not collected in the thyroid. Bromine can be used to label many organic molecules by methods analogous to radioiodination. The only North American source of Br-77 in the 70's and 80's was Los Alamos National Laboratory, but it discontinued production in 1989. In this method, a p,3n reaction on Br-77 produces Kr-77 which decays with a 1.2 hour half life to Br-77. A cyclotron generated 40 MeV proton beam is incident on a nearly saturated NaBr or LiBr solution contained in a copper or titanium target. A cooling chamber through which helium gas is flowed separates the solution from the cyclotron beam line. Helium gas is also flowed through the solution to extract Kr-77 gas. The mixture flows through a nitrogen trap where Kr-77 freezes and is allowed to decay to Br-77. Eight production runs were performed, three with a copper target and five with a titanium target with yields of 40, 104, 180, 679, 1080, 685, 762 and 118 uCi respectively. Gamma ray spectroscopy has shown the product to be very pure, however corrosion has been a major obstacle, causing the premature retirement of the copper target. Phantom and in-vivo rat nuclear images, and an autoradiograph in a rat are presented. The quality of the nuclear scans is reasonable and the autoradiograph reveals high isotope uptake in the renal parenchyma, a more moderate but uniform uptake in pulmonary and hepatic tissue, and low soft tissue uptake. There is no isotope uptake in the brain or the gastric mucosa. ^