979 resultados para Night vision devices.


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Although robotics research has seen advances over the last decades robots are still not in widespread use outside industrial applications. Yet a range of proposed scenarios have robots working together, helping and coexisting with humans in daily life. In all these a clear need to deal with a more unstructured, changing environment arises. I herein present a system that aims to overcome the limitations of highly complex robotic systems, in terms of autonomy and adaptation. The main focus of research is to investigate the use of visual feedback for improving reaching and grasping capabilities of complex robots. To facilitate this a combined integration of computer vision and machine learning techniques is employed. From a robot vision point of view the combination of domain knowledge from both imaging processing and machine learning techniques, can expand the capabilities of robots. I present a novel framework called Cartesian Genetic Programming for Image Processing (CGP-IP). CGP-IP can be trained to detect objects in the incoming camera streams and successfully demonstrated on many different problem domains. The approach requires only a few training images (it was tested with 5 to 10 images per experiment) is fast, scalable and robust yet requires very small training sets. Additionally, it can generate human readable programs that can be further customized and tuned. While CGP-IP is a supervised-learning technique, I show an integration on the iCub, that allows for the autonomous learning of object detection and identification. Finally this dissertation includes two proof-of-concepts that integrate the motion and action sides. First, reactive reaching and grasping is shown. It allows the robot to avoid obstacles detected in the visual stream, while reaching for the intended target object. Furthermore the integration enables us to use the robot in non-static environments, i.e. the reaching is adapted on-the- fly from the visual feedback received, e.g. when an obstacle is moved into the trajectory. The second integration highlights the capabilities of these frameworks, by improving the visual detection by performing object manipulation actions.

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This paper proposes new metrics and a performance-assessment framework for vision-based weed and fruit detection and classification algorithms. In order to compare algorithms, and make a decision on which one to use fora particular application, it is necessary to take into account that the performance obtained in a series of tests is subject to uncertainty. Such characterisation of uncertainty seems not to be captured by the performance metrics currently reported in the literature. Therefore, we pose the problem as a general problem of scientific inference, which arises out of incomplete information, and propose as a metric of performance the(posterior) predictive probabilities that the algorithms will provide a correct outcome for target and background detection. We detail the framework through which these predicted probabilities can be obtained, which is Bayesian in nature. As an illustration example, we apply the framework to the assessment of performance of four algorithms that could potentially be used in the detection of capsicums (peppers).

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Background Risky single occasion drinking (RSOD; 4 or more drinks in <6 h) more than doubles the risk of injury in young people (15 - 25 years). The potential role of smartphone apps in reducing RSOD in young people is yet to be explored. Objective: To describe the initial prototype testing of ‘Ray's Night Out’, a new iPhone app targeting RSOD in young people. Method Quantitative and qualitative methods were used to evaluate the quality, perceived utility, and acceptability of the app among nine young people (19e23 years). Results Participants reported Ray's Night Out had good to excellent levels of functionality and visual appeal, acceptable to good levels of entertainment, interest and information, and acceptable levels of customization and interactivity. Young people thought the app had high levels of youth appeal, would prompt users to think about their alcohol use limits, but was unlikely to motivate a change in alcohol use in its current form. Qualitative data provided several suggestions for improving the app. Conclusion Following revision, Ray's Night Out could provide an effective intervention for RSOD in non help-seeking young people. A randomized controlled trial is currently underway to test the final prototype of the app.

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The potential of using mobile devices to increase learner engagement within a small group of at-risk vocational education students was studied through a qualitative case study. It was found that the use of mobile devices could be a strategy educators may use to reduce the barriers these students often encounter within traditional classrooms. Notions of interactivity, ease of use, existing familiarity and fluency were found to be fundamental variables that were central to the group's use of mobile devices. The study provides direction for educators looking for innovative ways to engage students who struggle in a classroom situation.

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With the aim of finding simple methods for the fabrication of He II refilling devices, He II flow has been studied through filters made from various fine powders (oxides and metals, grain sizes in the range 0.05–2 μm) by compacting them under pressure. The results obtained for the different states of He II flow, especially in the “breakthrough” and “easy flow” range, are explained by the fountain effect, He II hydrodynamics and the choking effect. According to the results, pressedpowder filters can be classified into three groups with different flow characteristics, of which the “good transfer filters” with a behaviour neatly described by simple theory are suitable for use in He II refilling devices.

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Traditional comparisons between the capture efficiency of sampling devices have generally looked at the absolute differences between devices. We recommend that the signal-to-noise ratio be used when comparing the capture efficiency of benthic sampling devices. Using the signal-to-noise ratio rather than the absolute difference has the advantages that the variance is taken into account when determining how important the difference is, the hypothesis and minimum detectable difference can be made identical for all taxa, it is independent of the units used for measurement, and the sample-size calculation is independent of the variance. This new technique is illustrated by comparing the capture efficiency of a 0.05 m(2) van Veen grab and an airlift suction device, using samples taken from Heron and One Tree lagoons, Australia.

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The estimation of feed efficiency in beef cattle should be undertaken in the environment where the genetic potential of the animal is to be expressed. Consequently if cattle are to be pasture fed, there is a requirement for accurate feed intake measurements on individual animals in the field. This in turn requires the use of accurate faecal marker delivery systems.

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This study aims to help broaden the use of electronic portal imaging devices (EPIDs) for pre-treatment patient positioning verification, from photon-beam radiotherapy to photon- and electron-beam radiotherapy, by proposing and testing a method for acquiring clinicallyuseful EPID images of patient anatomy using electron beams, with a view to enabling and encouraging further research in this area. EPID images used in this study were acquired using all available beams from a linac configured to deliver electron beams with nominal energies of 6, 9, 12, 16 and 20 MeV, as well as photon beams with nominal energies of 6 and 10 MV. A widely-available heterogeneous, approximately-humanoid, thorax phantom was used, to provide an indication of the contrast and noise produced when imaging different types of tissue with comparatively realistic thicknesses. The acquired images were automatically calibrated, corrected for the effects of variations in the sensitivity of individual photodiodes, using a flood field image. For electron beam imaging, flood field EPID calibration images were acquired with and without the placement of blocks of water-equivalent plastic (with thicknesses approximately equal to the practical range of electrons in the plastic) placed upstream of the EPID, to filter out the primary electron beam, leaving only the bremsstrahlung photon signal. While the electron beam images acquired using a standard (unfiltered) flood field calibration were observed to be noisy and difficult to interpret, the electron beam images acquired using the filtered flood field calibration showed tissues and bony anatomy with levels of contrast and noise that were similar to the contrast and noise levels seen in the clinically acceptable photon beam EPID images. The best electron beam imaging results (highest contrast, signal-to-noise and contrast-to-noise ratios) were achieved when the images were acquired using the higher energy electron beams (16 and 20 MeV) when the EPID was calibrated using an intermediate (12 MeV) electron beam energy. These results demonstrate the feasibility of acquiring clinically-useful EPID images of patient anatomy using electron beams and suggest important avenues for future investigation, thus enabling and encouraging further research in this area. There is manifest potential for the EPID imaging method proposed in this work to lead to the clinical use of electron beam imaging for geometric verification of electron treatments in the future.

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This paper provides a comprehensive review of the vision-based See and Avoid problem for unmanned aircraft. The unique problem environment and associated constraints are detailed, followed by an in-depth analysis of visual sensing limitations. In light of such detection and estimation constraints, relevant human, aircraft and robot collision avoidance concepts are then compared from a decision and control perspective. Remarks on system evaluation and certification are also included to provide a holistic review approach. The intention of this work is to clarify common misconceptions, realistically bound feasible design expectations and offer new research directions. It is hoped that this paper will help us to unify design efforts across the aerospace and robotics communities.

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This study presents results from an experimental 10-day research charter that was designed to quantify the effects of a) a turtle excluder device (TED) and b) a radial escape section bycatch reduction device (BRD) and c) both devices together, on prawn and bycatch catch rates in the Queensland shallow water eastern king prawn (Penaeus plebejus) trawl fishery. The bycatch was comprised of 250 taxa, mainly gurnards, whiting, lizard fish, flathead, dragonets, portunid crabs, turretfish and flounders. The observed mean catch rates of bycatch and marketable eastern king prawns from the standard trawl net (i.e., net with no TED or BRD) used during the charter were 11.06 (se 0.90) kg per hectare swept by the trawl gear (ha-1) and 0.94 kg ha-1, respectively. For the range of depths sampled (20.1-90.7 m), bycatch catch rates declined significantly at a rate of 0.14 kg ha-1 for every 1 m increase in depth, while prawn catch rates were unaffected. When both the TED and radial escape section BRD were used together they resulted in a 24% reduction in total bycatch catch rate compared to a standard net, but at a 20% reduction in marketable prawn catch rate. The largest reductions were achieved for stout whiting Sillago robusta (57% reduction) and yellowtail scad Trachurus novaezelandiae (32% reduction). Multidimensional scaling and analysis of similarities revealed that bycatch assemblages differed significantly between depths and latitude, but not between the different combinations of bycatch reduction devices. Despite the lowered prawn catch rates, the reduced bycatch catch rates are promising, particularly for S. robusta which is not permitted to be retained by the prawn trawl fleet and yet experiences considerable incidental fishing mortality, and because it is targeted in a separate licensed commercial fishery.

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This paper describes a vision-only system for place recognition in environments that are tra- versed at different times of day, when chang- ing conditions drastically affect visual appear- ance, and at different speeds, where places aren’t visited at a consistent linear rate. The ma- jor contribution is the removal of wheel-based odometry from the previously presented algo- rithm (SMART), allowing the technique to op- erate on any camera-based device; in our case a mobile phone. While we show that the di- rect application of visual odometry to our night- time datasets does not achieve a level of perfor- mance typically needed, the VO requirements of SMART are orthogonal to typical usage: firstly only the magnitude of the velocity is required, and secondly the calculated velocity signal only needs to be repeatable in any one part of the environment over day and night cycles, but not necessarily globally consistent. Our results show that the smoothing effect of motion constraints is highly beneficial for achieving a locally consis- tent, lighting-independent velocity estimate. We also show that the advantage of our patch-based technique used previously for frame recogni- tion, surprisingly, does not transfer to VO, where SIFT demonstrates equally good performance. Nevertheless, we present the SMART system us- ing only vision, which performs sequence-base place recognition in extreme low-light condi- tions where standard 6-DOF VO fails and that improves place recognition performance over odometry-less benchmarks, approaching that of wheel odometry.

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Recent interest in affect and the body have mobilized a contemporary review of aesthetics and phenomenology within architecture to unpack how environments affect spatial experience. Emerging spatial studies within the neuro-sciences, and their implications for architectural research as raised by architectural theorists Juhani Pallasmaa (2014) and Harry Mallgrave (2013) has been well supported by a raft of scientists and institutions including the prestigious Salk Institute. Although there has been some headway in spatial studies of the vision impaired (Cattaneo et al, 2011) to understand the role of their non-visual systems in assisting navigation and location, little is discussed in terms of their other abilities in sensing particular qualities of space which impinge upon emotion. This paper reviews a collection of studies exploring face vision and echo-location, amongst others, which provide insight into what might be termed affective perception of the vision impaired, and how further interplay between this research and the architectural field can contribute new knowledge regarding space and affect. By engaging with themes from the Aesthetics, Phenomenology and indeed Neuro-science fields, the paper provides background of current and potential cross disciplinary research, and highlights the role wearable technologies can play in enhancing knowledge of affective spatial experience.

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This study investigated questions related to half-occlusion processing in human stereoscopic vision: (1) How does the depth location of a half-occluding figure affect the depth localization of adjacent monocular objects? (2) Is three-dimensional slant around vertical axis (geometric effect) affected by half-occlusion constraints? and (3) How the half-occlusion constraints and surface formation processes are manifested in stereoscopic capture? Our results showed that the depth localization of binocular objects affects the depth localization of discrete monocular objects. We also showed that the visual system has a preference for a frontoparallel surface interpretation if the half-occlusion configuration allows multiple interpretation alternatives. When the surface formation was constrained by textures, our results showed that a process of rematching spreading determines the resulting perception and that the spreading can be limited by illusory contours that support the presence of binocularly unmatched figures. The unmatched figures could be present, if the inducing figures producing the illusory surface contained binocular image differences that provided cues for quantitative da Vinci stereopsis. These findings provide evidence of the significant role of half-occlusions in stereoscopic processing.

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Sampling devices differing greatly in shape, size and operating condition have been used to collect air samples to determine rates of emission of volatile substances, including odour. However, physical chemistry principles, in particular the partitioning of volatile substances between two phases as explained by Henrys Law and the relationship between wind velocity and emission rate, suggests that different devices cannot be expected to provide equivalent emission rate estimates. Thus several problems are associated with the use of static and dynamic emission chambers, but the more turbulent devices such as wind tunnels do not appear to be subject to these problems. In general, the ability to relate emission rate estimates obtained from wind tunnel measurements to those derived from device-independent techniques supports the use of wind tunnels to determine emission rates that can be used as input data for dispersion models.

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Two commonly used sampling devices (a wind tunnel and the US EPA dynamic emission chamber), were used to collect paired samples of odorous air from a number of agricultural odour sources. The odour samples were assessed using triangular, forced-choice dynamic olfactometry. The odour concentration data was combined with the flushing rate data to calculate odour emission rates for both devices on all sources. Odour concentrations were consistently higher in samples collected with a flux chamber (ratio ranging from 10:7 to 5:1, relative to wind tunnel samples), whereas odour emission rates were consistently larger when derived from wind tunnels (ratio ranging from 60:1 to 240:1, relative to flux chamber values). A complex relationship existed between emission rate estimates derived from each device, apparently influenced by the nature of the emitting surface. These results have great significance for users of odour dispersion models, for which an odour emission rate is a key input parameter.