25 research outputs found

    Very High Resolution (VHR) Satellite Imagery: Processing and Applications

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    Recently, growing interest in the use of remote sensing imagery has appeared to provide synoptic maps of water quality parameters in coastal and inner water ecosystems;, monitoring of complex land ecosystems for biodiversity conservation; precision agriculture for the management of soils, crops, and pests; urban planning; disaster monitoring, etc. However, for these maps to achieve their full potential, it is important to engage in periodic monitoring and analysis of multi-temporal changes. In this context, very high resolution (VHR) satellite-based optical, infrared, and radar imaging instruments provide reliable information to implement spatially-based conservation actions. Moreover, they enable observations of parameters of our environment at greater broader spatial and finer temporal scales than those allowed through field observation alone. In this sense, recent very high resolution satellite technologies and image processing algorithms present the opportunity to develop quantitative techniques that have the potential to improve upon traditional techniques in terms of cost, mapping fidelity, and objectivity. Typical applications include multi-temporal classification, recognition and tracking of specific patterns, multisensor data fusion, analysis of land/marine ecosystem processes and environment monitoring, etc. This book aims to collect new developments, methodologies, and applications of very high resolution satellite data for remote sensing. The works selected provide to the research community the most recent advances on all aspects of VHR satellite remote sensing

    Robust Visual Odometry and Dynamic Scene Modelling

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    Image-based estimation of camera trajectory, known as visual odometry (VO), has been a popular solution for robot navigation in the past decade due to its low-cost and widely applicable properties. The problem of tracking self-motion as well as motion of objects in the scene using information from a camera is known as multi-body visual odometry and is a challenging task. The performance of VO is heavily sensitive to poor imaging conditions (i.e., direct sunlight, shadow and image blur), which limits its feasibility in many challenging scenarios. Current VO solutions can provide accurate camera motion estimation in largely static scene. However, the deployment of robotic systems in our daily lives requires systems to work in significantly more complex, dynamic environment. This thesis aims to develop robust VO solutions against two challenging cases, underwater and highly dynamic environments, by extensively analyzing and overcoming the difficulties in both cases to achieve accurate ego-motion estimation. Furthermore, to better understand and exploit dynamic scene information, this thesis also investigates the motion of moving objects in dynamic scene, and presents a novel way to integrate ego and object motion estimation into a single framework. In particular, the problem of VO in underwater is challenging due to poor imaging condition and inconsistent motion caused by water flow. This thesis intensively tests and evaluates possible solutions to the mentioned issues, and proposes a stereo underwater VO system that is able to robustly and accurately localize the autonomous underwater vehicle (AUV). Visual odometry in dynamic environment is challenging because dynamic parts of the scene violate the static world assumption fundamental in most classical visual odometry algorithms. If moving parts of a scene dominate the static scene, off-the-shelf VO systems either fail completely or return poor quality trajectory estimation. Most existing techniques try to simplify the problem by removing dynamic information. Arguably, in most scenarios, the dynamics corresponds to a finite number of individual objects that are rigid or piecewise rigid, and their motions can be tracked and estimated in the same way as the ego-motion. With this consideration, the thesis proposes a brand new way to model and estimate object motion, and introduces a novel multi-body VO system that addresses the problem of tracking of both ego and object motion in dynamic outdoor scenes. Based on the proposed multi-body VO framework, this thesis also exploits the spatial and temporal relationships between the camera and object motions, as well as static and dynamic structures, to obtain more consistent and accurate estimations. To this end, the thesis introduces a novel visual dynamic object-aware SLAM system, that is able to achieve robust multiple moving objects tracking, accurate estimation of full SE(3) object motions, and extract inherent linear velocity information of moving objects, along with an accurate robot localisation and mapping of environment structure. The performance of the proposed system is demonstrated on real datasets, showing its capability to resolve rigid object motion estimation and yielding results that outperform state-of-the-art algorithms by an order of magnitude in urban driving scenarios

    Spatiotemporal enabled Content-based Image Retrieval

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    Children’s gaze behaviour at real-world and simulated road crossings

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    Children and older adults are overrepresented in pedestrian accidents (Department for Transport, 2010a, 2010b). Gaze behaviour is cited as a contributing factor in the majority of such accidents (Department for Transport, 2010a, 2010b); however, remarkably little is known about how children, adults and older adults control their gaze during either real or simulated road-crossing tasks. Because evidence suggests that behaviour in the laboratory may not accurately reflect that in more realistic situations (Dicks et al., 2010; ‘t Hart et al., 2009), this thesis used a real-world, active road-crossing task to compare, for the first time, how pedestrians across the lifespan direct their gaze during real road crossing. A total of 70 participants took part in the studies: 42 children (mean age 8.6 yrs, SD = 0.4); 14 young adults (mean age 24.1 yrs, SD = 4.5) and 14 older adults (mean age 70.7 yrs, SD = 4.1). In the first experiment, participants were escorted on a short walk while wearing a mobile eye tracker and asked to cross the roads along the way when they felt it was safe to do so. Gaze behaviour during the last 3 seconds before crossing the road at a signalised crossing was analysed. Both children and older adults directed their gaze significantly less often to traffic-relevant features (such as the road and vehicles) than young adults. However, their gaze patterns were very different. Older adults looked more at the ground ahead of them, which most likely reflects a functional adaptation to reduce the risk of tripping and falling as falls represent a serious risk in this population (Jensen, 1999). Children fixated traffic-irrelevant features more, which may indicate poorer attentional control or insufficient practice or experience. A serendipitous finding from this study was that the presence of a distractor (ice cream) acted to further draw attention away from the direction of oncoming vehicles in the sample of children. Based on these findings, a subsequent aim of the thesis was to explore whether two road-crossing training interventions (Crossroads and Safety Watch) would improve the amount of time children fixated traffic-relevant features of the environment: neither programme was found to have a significant impact on gaze behaviour compared to the control condition (no intervention). Another aim of the thesis that followed from the results of the first experiment was to further examine the attentional control of gaze behaviour in children. Two simulated road-crossings were purposely developed in the laboratory, allowing more controlled investigation of gaze behaviour at (simulated) signalised and unsignalised crossings, with and without a non-spatial secondary task (counting in threes). It was found that the addition of this secondary task affected children’s gaze behaviour in one of the simulation types but not the other. This demonstrated that cognitive processes are context dependent and not invariant across conditions. In light of the growing concern raised with respect to the use of artificial laboratory settings and tasks, the final aim of this thesis was to compare gaze behaviour of children under three display conditions: monitor simulation, projector simulation, and real-world; the results suggested that behaviour in the laboratory did not correspond with real-world behaviour. In real road-crossing situations, children looked significantly more often at the ground ahead of them (walkway) and at lights and signs than when performing in the “monitor” or “projector” simulations. These findings further emphasise the context-dependence of cognition and behaviour. This thesis contributes to the argument that a real-world setting provides rich and meaningful data and that, although the laboratory setting has certain methodological advantages, transfer of laboratory findings to the real-world context cannot be assumed. Similarly, road-crossing skills trained in a simulated setting (on a computer) do not appear to transfer to the real-world context. This thesis therefore advocates a real-world approach to the research and training of behaviour and underlying cognitive processes

    EG-ICE 2021 Workshop on Intelligent Computing in Engineering

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    The 28th EG-ICE International Workshop 2021 brings together international experts working at the interface between advanced computing and modern engineering challenges. Many engineering tasks require open-world resolutions to support multi-actor collaboration, coping with approximate models, providing effective engineer-computer interaction, search in multi-dimensional solution spaces, accommodating uncertainty, including specialist domain knowledge, performing sensor-data interpretation and dealing with incomplete knowledge. While results from computer science provide much initial support for resolution, adaptation is unavoidable and most importantly, feedback from addressing engineering challenges drives fundamental computer-science research. Competence and knowledge transfer goes both ways

    EG-ICE 2021 Workshop on Intelligent Computing in Engineering

    Get PDF
    The 28th EG-ICE International Workshop 2021 brings together international experts working at the interface between advanced computing and modern engineering challenges. Many engineering tasks require open-world resolutions to support multi-actor collaboration, coping with approximate models, providing effective engineer-computer interaction, search in multi-dimensional solution spaces, accommodating uncertainty, including specialist domain knowledge, performing sensor-data interpretation and dealing with incomplete knowledge. While results from computer science provide much initial support for resolution, adaptation is unavoidable and most importantly, feedback from addressing engineering challenges drives fundamental computer-science research. Competence and knowledge transfer goes both ways

    Proceedings. 9th 3DGeoInfo Conference 2014, [11-13 November 2014, Dubai]

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    It is known that, scientific disciplines such as geology, geophysics, and reservoir exploration intrinsically use 3D geo-information in their models and simulations. However, 3D geo-information is also urgently needed in many traditional 2D planning areas such as civil engineering, city and infrastructure modeling, architecture, environmental planning etc. Altogether, 3DGeoInfo is an emerging technology that will greatly influence the market within the next few decades. The 9th International 3DGeoInfo Conference aims at bringing together international state-of-the-art researchers and practitioners facilitating the dialogue on emerging topics in the field of 3D geo-information. The conference in Dubai offers an interdisciplinary forum of sub- and above-surface 3D geo-information researchers and practitioners dealing with data acquisition, modeling, management, maintenance, visualization, and analysis of 3D geo-information
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