61 resultados para swd: Camera


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Optical imaging techniques have played a major role in understanding the flow dynamics of varieties of fluid flows, particularly in the study of hypersonic flows. Schlieren and shadowgraph techniques have been the flow diagnostic tools for the investigation of compressible flows since more than a century. However these techniques provide only the qualitative information about the flow field. Other optical techniques such as holographic interferometry and laser induced fluorescence (LIF) have been used extensively for extracting quantitative information about the high speed flows. In this paper we present the application of digital holographic interferometry (DHI) technique integrated with short duration hypersonic shock tunnel facility having 1 ms test time, for quantitative flow visualization. Dynamics of the flow fields in hypersonic/supersonic speeds around different test models is visualized with DHI using a high-speed digital camera (0.2 million fps). These visualization results are compared with schlieren visualization and CFD simulation results. Fringe analysis is carried out to estimate the density of the flow field.

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In this paper, we present a machine learning approach for subject independent human action recognition using depth camera, emphasizing the importance of depth in recognition of actions. The proposed approach uses the flow information of all 3 dimensions to classify an action. In our approach, we have obtained the 2-D optical flow and used it along with the depth image to obtain the depth flow (Z motion vectors). The obtained flow captures the dynamics of the actions in space time. Feature vectors are obtained by averaging the 3-D motion over a grid laid over the silhouette in a hierarchical fashion. These hierarchical fine to coarse windows capture the motion dynamics of the object at various scales. The extracted features are used to train a Meta-cognitive Radial Basis Function Network (McRBFN) that uses a Projection Based Learning (PBL) algorithm, referred to as PBL-McRBFN, henceforth. PBL-McRBFN begins with zero hidden neurons and builds the network based on the best human learning strategy, namely, self-regulated learning in a meta-cognitive environment. When a sample is used for learning, PBLMcRBFN uses the sample overlapping conditions, and a projection based learning algorithm to estimate the parameters of the network. The performance of PBL-McRBFN is compared to that of a Support Vector Machine (SVM) and Extreme Learning Machine (ELM) classifiers with representation of every person and action in the training and testing datasets. Performance study shows that PBL-McRBFN outperforms these classifiers in recognizing actions in 3-D. Further, a subject-independent study is conducted by leave-one-subject-out strategy and its generalization performance is tested. It is observed from the subject-independent study that McRBFN is capable of generalizing actions accurately. The performance of the proposed approach is benchmarked with Video Analytics Lab (VAL) dataset and Berkeley Multimodal Human Action Database (MHAD). (C) 2013 Elsevier Ltd. All rights reserved.

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Large animals are disproportionately likely to go extinct, and the effects of this on ecosystem processes are unclear. Megaherbivores (weighing over 1000kg) are thought to be particularly effective seed dispersers, yet only a few plant species solely or predominantly adapted for dispersal by megaherbivores have been identified. The reasons for this paradox may be elucidated by examining the ecology of so-called megafaunal fruiting species in Asia, where large-fruited species have been only sparsely researched. We conducted focal tree watches, camera trapping, fruit ageing trials, dung seed counts and germination trials to understand the ecology of Dillenia indica, a large-fruited species thought to be elephant-dispersed, in a tropical moist forest (Buxa Tiger Reserve, India). We find that the initial hardness of the fruit of D.indica ensures that its small (6mm) seeds will primarily be consumed and dispersed by elephants and perhaps other megaherbivores. Elephants removed 63.3% of camera trap-monitored fruits taken by frugivores. If the fruit of D.indica is not removed by a large animal, the seeds of D.indica become available to successively smaller frugivores as its fruits soften. Seeds from both hard and soft fruits are able to germinate, meaning these smaller frugivores may provide a mechanism for dispersal without megaherbivores.Synthesis. Dillenia indica's strategy for dispersal allows it to realize the benefits of dispersal by megaherbivores without becoming fully reliant on these less abundant species. This risk-spreading dispersal behaviour suggests D.indica will be able to persist even if its megafaunal disperser becomes extinct.

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In this paper we present an approach to build a prototype. model of a first-responder localization system intended for disaster relief operations. This system is useful to monitor and track the positions of the first-responders in an indoor environment, where GPS is not available. Each member of the first responder team is equipped with two zero-velocity-update-aided inertial navigation systems, one on each foot, a camera mounted on a helmet, and a processing platform strapped around the waist of the first responder, which fuses the data from the different sensors. The fusion algorithm runs real-time on the processing platform. The video is also processed using the DSP core of the computing machine. The processed data consisting of position, velocity, heading information along with video streams is transmitted to the command and control system via a local infrastructure WiFi network. A centralized cooperative localization algorithm, utilizing the information from Ultra Wideband based inter-agent ranging devices combined with the position estimates and uncertainties of each first responder, has also been implemented.

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Blends of conventional fuels such as Jet-A1 (aviation kerosene) and diesel with bio-derived components, referred to as biofttels, are gradually replacing the conventional fuels in aircraft and automobile engines. There is a lack of understanding on the interaction of spray drops of such biofuels with solid surfaces. The present study is an experimental investigation on the impact of biofuel drops onto a smooth stainless steel surface. The biofuel is a mixture of 90% commercially available camelina-derived biofuel and 10% aromatics. Biofuel drops were generated using a syringe-hypodermic needle arrangement. On demand, the needle delivers an almost spherical drop with drop diameter in the range 2.05-2.15 mm. Static wetting experiments show that the biofuel drop completely wets the stainless steel surface and exhibits an equilibrium contact angle of 5.6. High speed video camera was used to capture the impact dynamics of biofuel drops with Weber number ranging from 20 to 570. The spreading dynamics and maximum spreading diameter of impacting biofuel drops on the target surface were analyzed. For the impact of high Weber number biofuel drops, the spreading law suggests beta similar to tau(0.5) where beta is the spread factor and tau, the nondimensionalized time. The experimentally observed trend of maximum spread factor, beta(max) of camelina biofuel drop on the target surface with We compares well with the theoretically predicted trend from Ukiwe-Kwok model. After reaching beta(max), the impacting biofuel drop undergoes a prolonged sluggish spreading due to the high wetting nature of the camelina biofuel-stainless steel system. As a result, the final spread factor is found to be a little more than beta(max). (C) 2014 Elsevier Inc. All rights reserved.

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A micro-newton static force sensor is presented here as a packaged product. The sensor, which is based on the mechanics of deformable objects, consists of a compliant mechanism that amplifies the displacement caused by the force that is to be measured. The output displacement, captured using a digital microscope and analyzed using image processing techniques, is used to calculate the force using precalibrated force-displacement curve. Images are scanned in real time at a frequency of 15 frames per second and sampled at around half the scanning frequency. The sensor was built, packaged, calibrated, and tested. It has simulated and measured stiffness values of 2.60N/m and 2.57N/m, respectively. The smallest force it can reliably measure in the presence of noise is about 2 mu N over a range of 1.4mN. The off-the-shelf digital microscope aside, all of its other components are purely mechanical; they are inexpensive and can be easily made using simple machines. Another highlight of the sensor is that its movable and delicate components are easily replaceable. The sensor can be used in aqueous environment as it does not use electric, magnetic, thermal, or any other fields. Currently, it can only measure static forces or forces that vary at less than 1Hz because its response time and bandwidth are limited by the speed of imaging with a camera. With a universal serial bus (USB) connection of its digital microscope, custom-developed graphical user interface (GUI), and related software, the sensor is fully developed as a readily usable product.

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A new technique based on luminescent molecular sensors is utilized in these series of experiments for measurement of temperatures in material removal processes. 2-Dimensional machining of metals at low speeds and surface grinding configurations are used as the model experimental systems to understand the efficacy of this experimental technique. The experiments were conducted with a series of luminescent sensors and binder combinations for the temperature measurement. The luminescence of the sensor was measured through a charge-coupled device imaging camera, and intensive calibration exercises were performed on these sensors. Excellent agreement in the temperature fields measured through this new experimental approach and traditional infrared thermography is seen here. This technique offers the unique capability of allowing measurement of temperatures in the presence of a lubricant, akin to manufacturing conditions in situ. Extension of the technique to measure the temperature field at the tool-chip contact is described.

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In the present work, the spray structure of diesel from a 200-mu m, single-hole solenoid injector is studied using microscopic imaging at injection pressures of 700, 1000 and 1400 bar for various gas pressures. A long-distance microscope with a high resolution camera is used for spray visualization with a direct imaging technique. This study shows that even at very high injection pressures, the spray structure in an ambient environment of atmospheric pressure reveals presence of entangled ligaments and non-spherical droplets during the injection period. With increase in the injection pressure, the ligaments tend to get smaller and spread radially. The spray structure studies are also conducted at high gas pressures in a specially designed high pressure chamber with optical access. The near nozzle spray structure at the end of the injection shows that the liquid jet breakup is improved with increase in gas density. The droplet size measurement is possible only late in the injection duration when the breakup appears to be complete and mostly spherical droplets are observed. Hence, droplet size measurements are performed after 1.3 ms from start of the injection pulse. Spatial and temporal variation in Sauter Mean `Diameter (SMD) is observed and reported for the case corresponding to an injection pressure of 700 bar. Overall, this study has highlighted the importance of verifying the extentof atomization and droplet shape even in dense sprays before using conventional dropsizing methods such as PDPA.

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GX 301-2, a bright high-mass X-ray binary with an orbital period of 41.5 d, exhibits stable periodic orbital intensity modulations with a strong pre-periastron X-ray flare. Several models have been proposed to explain the accretion at different orbital phases, invoking accretion via stellar wind, equatorial disc, and accretion stream from the companion star. We present results from exhaustive orbital phase resolved spectroscopic measurements of GX 301-2 using data from the Gas Slit Camera onboard MAXI. Using spectroscopic analysis of the MAXI data with unprecedented orbital coverage for many orbits continuously, we have found a strong orbital dependence of the absorption column density and equivalent width of the iron emission line. A very large equivalent width of the iron line along with a small value of the column density in the orbital phase range 0.10-0.30 after the periastron passage indicates the presence of high density absorbing matter behind the neutron star in this orbital phase range. A low energy excess is also found in the spectrum at orbital phases around the pre-periastron X-ray flare. The orbital dependence of these parameters are then used to examine the various models about mode of accretion on to the neutron star in GX 301-2.

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H. 264/advanced video coding surveillance video encoders use the Skip mode specified by the standard to reduce bandwidth. They also use multiple frames as reference for motion-compensated prediction. In this paper, we propose two techniques to reduce the bandwidth and computational cost of static camera surveillance video encoders without affecting detection and recognition performance. A spatial sampler is proposed to sample pixels that are segmented using a Gaussian mixture model. Modified weight updates are derived for the parameters of the mixture model to reduce floating point computations. A storage pattern of the parameters in memory is also modified to improve cache performance. Skip selection is performed using the segmentation results of the sampled pixels. The second contribution is a low computational cost algorithm to choose the reference frames. The proposed reference frame selection algorithm reduces the cost of coding uncovered background regions. We also study the number of reference frames required to achieve good coding efficiency. Distortion over foreground pixels is measured to quantify the performance of the proposed techniques. Experimental results show bit rate savings of up to 94.5% over methods proposed in literature on video surveillance data sets. The proposed techniques also provide up to 74.5% reduction in compression complexity without increasing the distortion over the foreground regions in the video sequence.

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Cell-phone based imaging flow cytometry can be realized by flowing cells through the microfluidic devices, and capturing their images with an optically enhanced camera of the cell-phone. Throughput in flow cytometers is usually enhanced by increasing the flow rate of cells. However, maximum frame rate of camera system limits the achievable flow rate. Beyond this, the images become highly blurred due to motion-smear. We propose to address this issue with coded illumination, which enables recovery of high-fidelity images of cells far beyond their motion-blur limit. This paper presents simulation results of deblurring the synthetically generated cell/bead images under such coded illumination.

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We propose to develop a 3-D optical flow features based human action recognition system. Optical flow based features are employed here since they can capture the apparent movement in object, by design. Moreover, they can represent information hierarchically from local pixel level to global object level. In this work, 3-D optical flow based features a re extracted by combining the 2-1) optical flow based features with the depth flow features obtained from depth camera. In order to develop an action recognition system, we employ a Meta-Cognitive Neuro-Fuzzy Inference System (McFIS). The m of McFIS is to find the decision boundary separating different classes based on their respective optical flow based features. McFIS consists of a neuro-fuzzy inference system (cognitive component) and a self-regulatory learning mechanism (meta-cognitive component). During the supervised learning, self-regulatory learning mechanism monitors the knowledge of the current sample with respect to the existing knowledge in the network and controls the learning by deciding on sample deletion, sample learning or sample reserve strategies. The performance of the proposed action recognition system was evaluated on a proprietary data set consisting of eight subjects. The performance evaluation with standard support vector machine classifier and extreme learning machine indicates improved performance of McFIS is recognizing actions based of 3-D optical flow based features.

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The present study discusses the photosensitivity of GeS2 chalcogenide glass in response to irradiation with femtosecond pulses at 1047 nm. Bulk GeS2 glasses are prepared by conventional melt quenching technique and the amorphous nature of the glass is confirmed using X-ray diffraction. Ultrafast laser inscription technique is used to fabricate the straight channel waveguides in the glass. Single scan and multi scan waveguides are inscribed in GeS2 glasses of length 0.65 cm using a master oscillator power amplifier Yb doped fiber laser (IMRA mu jewel D400) with different pulse energy and translation speed. Diameters of the inscribed waveguides are measured and its dependence on the inscription parameters such as translation speed and pulse energy is studied. Butt coupling method is used to characterize the loss measurement of the inscribed optical waveguides. The mode field image of the waveguides is captured using CCD camera and compared with the mode field image of a standard SMF-28 fibers.

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One-dimensional transient heat flow is interpreted as a procession of `macro-scale translatory motion of indexed isothermal surfaces'. A new analytical model is proposed by introducing velocity of isothermal surface in Fourier heat diffusion equation. The velocity dependent function is extracted by revisiting `the concept of thermal layer of heat conduction in solid' and `exact solution' to estimate thermal diffusivity. The experimental approach involves establishment of 1 D unsteady heat flow inside the sample through Step-temperature excitation. A novel self-reference interferometer is utilized to separate a `unique isothermal surface' in time-varying temperature field. The translatory motion of the said isothermal surface is recorded using digital camera to estimate its velocity. From the knowledge of thermo-optic coefficient, temperature of the said isothermal surface is predicted. The performance of proposed method is evaluated for Quartz sample and compared with literature.

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Large animal species are prone to local extirpation, but ecologists cannot yet predict how the loss of megaherbivores affects ecosystem processes such as seed dispersal. Few studies have compared the quantity and quality of seed dispersal by megaherbivores versus alternative frugivores in the wild, particularly for plant species with fruit easily consumed by many frugivorous species. In a disturbed tropical moist forest in India, we examine whether megaherbivores are a major frugivore of two tree species with easily edible, mammal-dispersed fruit. We quantify the relative fruit removal rates of Artocarpus chaplasha and Careya arborea, by the Asian elephant (Elephas maximus) and alternative dispersers. Through focal watches and camera trapping, we found the elephant to be amongst the top three frugivores for each tree species. Furthermore, seed transects under A. chaplasha show that arboreal frugivores discard seeds only a short distance from the parental tree, underscoring the elephant's role as a long-distance disperser. Our data provide unprecedented support for an old notion: megaherbivores may be key dispersers for a broad set of mammal-dispersed fruiting species, and not just fruit inaccessible to smaller frugivores. As such, the elephant may be particularly important for the functional ecology of the disturbed forests it still inhabits across tropical Asia.