924 resultados para Long Visual Fibres


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The International Journal of Robotics Research (IJRR) has a long history of publishing the state-of-the-art in the field of robotic vision. This is the fourth special issue devoted to the topic. Previous special issues were published in 2012 (Volume 31, No. 4), 2010 (Volume 29, Nos 2–3) and 2007 (Volume 26, No. 7, jointly with the International Journal of Computer Vision). In a closely related field was the special issue on Visual Servoing published in IJRR, 2003 (Volume 22, Nos 10–11). These issues nicely summarize the highlights and progress of the past 12 years of research devoted to the use of visual perception for robotics.

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This paper presents visual detection and classification of light vehicles and personnel on a mine site.We capitalise on the rapid advances of ConvNet based object recognition but highlight that a naive black box approach results in a significant number of false positives. In particular, the lack of domain specific training data and the unique landscape in a mine site causes a high rate of errors. We exploit the abundance of background-only images to train a k-means classifier to complement the ConvNet. Furthermore, localisation of objects of interest and a reduction in computation is enabled through region proposals. Our system is tested on over 10km of real mine site data and we were able to detect both light vehicles and personnel. We show that the introduction of our background model can reduce the false positive rate by an order of magnitude.

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Uncorrected refractive error, including astigmatism, is a leading cause of reversible visual impairment. While the ability to perform vision-related daily activities is reduced when people are not optimally corrected, only limited research has investigated the impact of uncorrected astigmatism. Given the capacity to perform vision-related daily activities involves integration of a range of visual and cognitive cues, this research examined the impact of simulated astigmatism on visual tasks that also involved cognitive input. The research also examined whether the higher levels of complexity inherent in Chinese characters makes them more susceptible to the effects of astigmatism. The effects of different powers of astigmatism, as well as astigmatism at different axes were investigated in order to determine the minimum level of astigmatism that resulted in a decrement in visual performance.

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This article is a work of non-fiction which draws on my research in football fiction.

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Due to the numerous possibilities of voicing concerns and the flood of data we are exposed to, local issues are sometimes at risk of being overlooked. This study explores Local Commons, a design intervention in public space that combines situated digital and tangible media in order to engage communities in contributing and debating different perspectives on a given local issue. The intervention invited the community to submit images of their perspectives on the issue, which were displayed on a public screen. Via tangible buttons in front of the screen, community members then agree or disagree on the displayed perspectives, creating a space for deliberation. In a user study, we were specifically interested in testing three aspects of our intervention, which are discussed in this paper: The difference that situatedness, visual content, and tangible interaction can make to urban community engagement.

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This research investigated the visual demands in modern primary school classrooms and also the impact of common refractive anomalies on a child's ability to perform academic-related tasks. The results showed that relatively high levels of visual acuity, contrast demand and sustained accommodative-convergence are required to perform optimally in the modern classroom environment. It was also demonstrated that relatively low magnitudes of uncorrected refractive error may have a detrimental impact on children's ability to perform academic-related activities at school, with sustained near work further exacerbating this effect. These findings have important implications for both eye care practitioners and education authorities.

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This project developed a visual strategy and graphic outcomes to communicate the results of a scientific collaborative project to the Mackay community. During 2013 and 2014 a team from CSIRO engaged with the community in Mackay to collaboratively develop a set of strategies to improve the management of the Great Barrier Reef. The result of this work was a 300+ page scientific report that needed to be translated and summarised to the general community. The aim of this project was to strategically synthesise information contained in the report and to design and produce an outcome to be distributed to the participant community. By working with the CISRO researchers, an action toolkit was developed, with twelve cards and a booklet. Each card represented the story behind a certain local management issue and the actions that the participants suggested should be taken in order to improve management of The Reef. During the design synthesis it was identified that for all management issues there was a reference to the need to develop some sort of "educational campaign" to the area. That was then translated as an underlying action to support all other actions proposed in the toolkit.

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A large range of underground mining equipment makes use of compliant hydraulic arms for tasks such as rock-bolting, rock breaking, explosive charging and shotcreting. This paper describes a laboratory model electo-hydraulic manipulator which is used to prototype novel control and sensing techniques. The research is aimed at improving the safety and productivity of these mining tasks through automation, in particular the application of closed-loop visual positioning of the machine's end-effector.

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We propose a novel technique for conducting robust voice activity detection (VAD) in high-noise recordings. We use Gaussian mixture modeling (GMM) to train two generic models; speech and non-speech. We then score smaller segments of a given (unseen) recording against each of these GMMs to obtain two respective likelihood scores for each segment. These scores are used to compute a dissimilarity measure between pairs of segments and to carry out complete-linkage clustering of the segments into speech and non-speech clusters. We compare the accuracy of our method against state-of-the-art and standardised VAD techniques to demonstrate an absolute improvement of 15% in half-total error rate (HTER) over the best performing baseline system and across the QUT-NOISE-TIMIT database. We then apply our approach to the Audio-Visual Database of American English (AVDBAE) to demonstrate the performance of our algorithm in using visual, audio-visual or a proposed fusion of these features.

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Insulated Rail Joints (IRJs) are safety critical component of the automatic block signalling and broken rail detection systems. IRJs exhibit several failure modes due to complex interaction between the railhead ends and the wheel tread near the gap. These localised zones could not be monitored using automatic sensing devices and hence are resorted to visual inspection only, which is error prone and expensive. In Australia alone currently there are 50,000 IRJs across 80,000 km of rail track. The significance of the problem around the world could thus be realised as there exists one IRJ for each 1.6 km track length. IRJs exhibit extremely low and variable service life; further the track substructure underneath IRJs degrade faster. Thus presence of the IRJs incur significant costs to track maintenance. IRJ failures have also contributed to some train derailments and various traffic disruptions in rail lines. This paper reports a systematic research carried out over seven years on the mechanical behaviour of IRJs for practically relevant outcomes. The research has scientifically established that stiffening the track bed for reduction in impact force is an ill-conceived concept and the most effective method is to reduce the gap size. Further it is established that hardening the railhead ends through laser coating (or other) cannot adequately address the metal flow problem in the long run; modification of the railhead profile is the only appropriate technique to completely eliminate the problem. Part of these outcomes has been adopted by the rail infrastructure owners in Australia.

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The paper critiques the focus of creative industries policy on capability development of small and medium sized firms and the provision of regional incentives. It analyses factors affecting the competitiveness and sustainability of the games development industry and visual effects suppliers to feature films. Interviews with participants in these industries highlight the need for policy instruments to take into consideration the structure and organization of global markets and the power of lead multinational corporations. We show that although forms of economic governance in these industries may allow sustainable value capture, they are interrupted by bottlenecks in which ferocious competition among suppliers is confronted by comparatively little competition among the lead firms. We argue that current approaches to creative industries policy aimed at building self-sustaining creative industries are unlikely to be sufficient because of the globalized nature of the industries. Rather, we argue that a more profitable approach is likely to require supporting diversification of the industries as ‘feeders’ into other areas of the economy.

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Visual information in the form of lip movements of the speaker has been shown to improve the performance of speech recognition and search applications. In our previous work, we proposed cross database training of synchronous hidden Markov models (SHMMs) to make use of external large and publicly available audio databases in addition to the relatively small given audio visual database. In this work, the cross database training approach is improved by performing an additional audio adaptation step, which enables audio visual SHMMs to benefit from audio observations of the external audio models before adding visual modality to them. The proposed approach outperforms the baseline cross database training approach in clean and noisy environments in terms of phone recognition accuracy as well as spoken term detection (STD) accuracy.

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Spoken term detection (STD) is the task of looking up a spoken term in a large volume of speech segments. In order to provide fast search, speech segments are first indexed into an intermediate representation using speech recognition engines which provide multiple hypotheses for each speech segment. Approximate matching techniques are usually applied at the search stage to compensate the poor performance of automatic speech recognition engines during indexing. Recently, using visual information in addition to audio information has been shown to improve phone recognition performance, particularly in noisy environments. In this paper, we will make use of visual information in the form of lip movements of the speaker in indexing stage and will investigate its effect on STD performance. Particularly, we will investigate if gains in phone recognition accuracy will carry through the approximate matching stage to provide similar gains in the final audio-visual STD system over a traditional audio only approach. We will also investigate the effect of using visual information on STD performance in different noise environments.

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Speech recognition can be improved by using visual information in the form of lip movements of the speaker in addition to audio information. To date, state-of-the-art techniques for audio-visual speech recognition continue to use audio and visual data of the same database for training their models. In this paper, we present a new approach to make use of one modality of an external dataset in addition to a given audio-visual dataset. By so doing, it is possible to create more powerful models from other extensive audio-only databases and adapt them on our comparatively smaller multi-stream databases. Results show that the presented approach outperforms the widely adopted synchronous hidden Markov models (HMM) trained jointly on audio and visual data of a given audio-visual database for phone recognition by 29% relative. It also outperforms the external audio models trained on extensive external audio datasets and also internal audio models by 5.5% and 46% relative respectively. We also show that the proposed approach is beneficial in noisy environments where the audio source is affected by the environmental noise.

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We investigated functional, morphological and molecular adaptations to strength training exercise and cold water immersion (CWI) through two separate studies. In one study, 21 physically active men strength trained for 12 weeks (2 d⋅wk–1), with either 10 min of CWI or active recovery (ACT) after each training session. Strength and muscle mass increased more in the ACT group than in the CWI group (P<0.05). Isokinetic work (19%), type II muscle fibre cross-sectional area (17%) and the number of myonuclei per fibre (26%) increased in the ACT group (all P<0.05) but not the CWI group. In another study, nine active men performed a bout of single-leg strength exercises on separate days, followed by CWI or ACT. Muscle biopsies were collected before and 2, 24 and 48 h after exercise. The number of satellite cells expressing neural cell adhesion molecule (NCAM) (10−30%) and paired box protein (Pax7)(20−50%) increased 24–48 h after exercise with ACT. The number of NCAM+ satellitecells increased 48 h after exercise with CWI. NCAM+- and Pax7+-positivesatellite cell numbers were greater after ACT than after CWI (P<0.05). Phosphorylation of p70S6 kinaseThr421/Ser424 increased after exercise in both conditions but was greater after ACT (P<0.05). These data suggest that CWI attenuates the acute changes in satellite cell numbers and activity of kinases that regulate muscle hypertrophy, which may translate to smaller long-term training gains in muscle strength and hypertrophy. The use of CWI as a regular post-exercise recovery strategy should be reconsidered.