167,451 research outputs found

    Using Augmented Reality as a Medium to Assist Teaching in Higher Education

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    In this paper we describe the use of a high-level augmented reality (AR) interface for the construction of collaborative educational applications that can be used in practice to enhance current teaching methods. A combination of multimedia information including spatial three-dimensional models, images, textual information, video, animations and sound, can be superimposed in a student-friendly manner into the learning environment. In several case studies different learning scenarios have been carefully designed based on human-computer interaction principles so that meaningful virtual information is presented in an interactive and compelling way. Collaboration between the participants is achieved through use of a tangible AR interface that uses marker cards as well as an immersive AR environment which is based on software user interfaces (UIs) and hardware devices. The interactive AR interface has been piloted in the classroom at two UK universities in departments of Informatics and Information Science

    Loss Guided Activation for Action Recognition in Still Images

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    One significant problem of deep-learning based human action recognition is that it can be easily misled by the presence of irrelevant objects or backgrounds. Existing methods commonly address this problem by employing bounding boxes on the target humans as part of the input, in both training and testing stages. This requirement of bounding boxes as part of the input is needed to enable the methods to ignore irrelevant contexts and extract only human features. However, we consider this solution is inefficient, since the bounding boxes might not be available. Hence, instead of using a person bounding box as an input, we introduce a human-mask loss to automatically guide the activations of the feature maps to the target human who is performing the action, and hence suppress the activations of misleading contexts. We propose a multi-task deep learning method that jointly predicts the human action class and human location heatmap. Extensive experiments demonstrate our approach is more robust compared to the baseline methods under the presence of irrelevant misleading contexts. Our method achieves 94.06\% and 40.65\% (in terms of mAP) on Stanford40 and MPII dataset respectively, which are 3.14\% and 12.6\% relative improvements over the best results reported in the literature, and thus set new state-of-the-art results. Additionally, unlike some existing methods, we eliminate the requirement of using a person bounding box as an input during testing.Comment: Accepted to appear in ACCV 201

    An Introduction to 3D User Interface Design

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    3D user interface design is a critical component of any virtual environment (VE) application. In this paper, we present a broad overview of three-dimensional (3D) interaction and user interfaces. We discuss the effect of common VE hardware devices on user interaction, as well as interaction techniques for generic 3D tasks and the use of traditional two-dimensional interaction styles in 3D environments. We divide most user interaction tasks into three categories: navigation, selection/manipulation, and system control. Throughout the paper, our focus is on presenting not only the available techniques, but also practical guidelines for 3D interaction design and widely held myths. Finally, we briefly discuss two approaches to 3D interaction design, and some example applications with complex 3D interaction requirements. We also present an annotated online bibliography as a reference companion to this article

    Methodological Innovation in Practice-Based Design Doctorates

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    This article presents a selective review of recent design PhDs that identify and analyse the methodological innovation that is occurring in the field, in order to inform future provision of research training. Six recently completed design PhDs are used to highlight possible philosophical and practical models that can be adopted by future PhD students in design. Four characteristics were found in design PhD methodology: innovations in the format and structure of the thesis, a pick-and-mix approach to research design, situating practice in the inquiry, and the validation of visual analysis. The article concludes by offering suggestions on how research training can be improved. By being aware of recent methodological innovations in the field, design educators will be better informed when developing resources for future design doctoral candidates and assisting supervision teams in developing a more informed and flexible approach to practice-based research

    Interaction Design: Foundations, Experiments

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    Interaction Design: Foundations, Experiments is the result of a series of projects, experiments and curricula aimed at investigating the foundations of interaction design in particular and design research in general. The first part of the book - Foundations - deals with foundational theoretical issues in interaction design. An analysis of two categorical mistakes -the empirical and interactive fallacies- forms a background to a discussion of interaction design as act design and of computational technology as material in design. The second part of the book - Experiments - describes a range of design methods, programs and examples that have been used to probe foundational issues through systematic questioning of what is given. Based on experimental design work such as Slow Technology, Abstract Information Displays, Design for Sound Hiders, Zero Expression Fashion, and IT+Textiles, this section also explores how design experiments can play a central role when developing new design theory

    Student Teaching and Research Laboratory Focusing on Brain-computer Interface Paradigms - A Creative Environment for Computer Science Students -

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    This paper presents an applied concept of a brain-computer interface (BCI) student research laboratory (BCI-LAB) at the Life Science Center of TARA, University of Tsukuba, Japan. Several successful case studies of the student projects are reviewed together with the BCI Research Award 2014 winner case. The BCI-LAB design and project-based teaching philosophy is also explained. Future teaching and research directions summarize the review.Comment: 4 pages, 4 figures, accepted for EMBC 2015, IEEE copyrigh

    Do (and say) as I say: Linguistic adaptation in human-computer dialogs

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    © Theodora Koulouri, Stanislao Lauria, and Robert D. Macredie. This article has been made available through the Brunel Open Access Publishing Fund.There is strong research evidence showing that people naturally align to each other’s vocabulary, sentence structure, and acoustic features in dialog, yet little is known about how the alignment mechanism operates in the interaction between users and computer systems let alone how it may be exploited to improve the efficiency of the interaction. This article provides an account of lexical alignment in human–computer dialogs, based on empirical data collected in a simulated human–computer interaction scenario. The results indicate that alignment is present, resulting in the gradual reduction and stabilization of the vocabulary-in-use, and that it is also reciprocal. Further, the results suggest that when system and user errors occur, the development of alignment is temporarily disrupted and users tend to introduce novel words to the dialog. The results also indicate that alignment in human–computer interaction may have a strong strategic component and is used as a resource to compensate for less optimal (visually impoverished) interaction conditions. Moreover, lower alignment is associated with less successful interaction, as measured by user perceptions. The article distills the results of the study into design recommendations for human–computer dialog systems and uses them to outline a model of dialog management that supports and exploits alignment through mechanisms for in-use adaptation of the system’s grammar and lexicon
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