24,068 research outputs found

    Augmented reality meeting table: a novel multi-user interface for architectural design

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    Immersive virtual environments have received widespread attention as providing possible replacements for the media and systems that designers traditionally use, as well as, more generally, in providing support for collaborative work. Relatively little attention has been given to date however to the problem of how to merge immersive virtual environments into real world work settings, and so to add to the media at the disposal of the designer and the design team, rather than to replace it. In this paper we report on a research project in which optical see-through augmented reality displays have been developed together with prototype decision support software for architectural and urban design. We suggest that a critical characteristic of multi user augmented reality is its ability to generate visualisations from a first person perspective in which the scale of rendition of the design model follows many of the conventions that designers are used to. Different scales of model appear to allow designers to focus on different aspects of the design under consideration. Augmenting the scene with simulations of pedestrian movement appears to assist both in scale recognition, and in moving from a first person to a third person understanding of the design. This research project is funded by the European Commission IST program (IST-2000-28559)

    New technologies for urban designers: the VENUE project

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    In this report, we first outline the basic idea of VENUE. This involves developing digital tools froma foundation of geographic information systems (GIS) software which we then apply to urbandesign, a subject area and profession which has little tradition in using such tools. Our project wasto develop two types of tool, namely functional analysis based on embedding models of movementin local environments into GIS based on ideas from the field of space syntax; and secondlyfashioning these ideas in a wider digital context in which the entire range of GIS technologies werebrought to bear at the local scale. By local scale, we mean the representation of urban environmentsfrom about 1: 500 to around 1: 2500

    Wearable learning tools

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    In life people must learn whenever and wherever they experience something new. Until recently computing technology could not support such a notion, the constraints of size, power and cost kept computers under the classroom table, in the office or in the home. Recent advances in miniaturization have led to a growing field of research in ‘wearable’ computing. This paper looks at how such technologies can enhance computer‐mediated communications, with a focus upon collaborative working for learning. An experimental system, MetaPark, is discussed, which explores communications, data retrieval and recording, and navigation techniques within and across real and virtual environments. In order to realize the MetaPark concept, an underlying network architecture is described that supports the required communication model between static and mobile users. This infrastructure, the MUON framework, is offered as a solution to provide a seamless service that tracks user location, interfaces to contextual awareness agents, and provides transparent network service switching

    Explore, Exploit or Listen: Combining Human Feedback and Policy Model to Speed up Deep Reinforcement Learning in 3D Worlds

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    We describe a method to use discrete human feedback to enhance the performance of deep learning agents in virtual three-dimensional environments by extending deep-reinforcement learning to model the confidence and consistency of human feedback. This enables deep reinforcement learning algorithms to determine the most appropriate time to listen to the human feedback, exploit the current policy model, or explore the agent's environment. Managing the trade-off between these three strategies allows DRL agents to be robust to inconsistent or intermittent human feedback. Through experimentation using a synthetic oracle, we show that our technique improves the training speed and overall performance of deep reinforcement learning in navigating three-dimensional environments using Minecraft. We further show that our technique is robust to highly innacurate human feedback and can also operate when no human feedback is given
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