371 research outputs found

    Computational interaction techniques for 3D selection, manipulation and navigation in immersive VR

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    3D interaction provides a natural interplay for HCI. Many techniques involving diverse sets of hardware and software components have been proposed, which has generated an explosion of Interaction Techniques (ITes), Interactive Tasks (ITas) and input devices, increasing thus the heterogeneity of tools in 3D User Interfaces (3DUIs). Moreover, most of those techniques are based on general formulations that fail in fully exploiting human capabilities for interaction. This is because while 3D interaction enables naturalness, it also produces complexity and limitations when using 3DUIs. In this thesis, we aim to generate approaches that better exploit the high potential human capabilities for interaction by combining human factors, mathematical formalizations and computational methods. Our approach is focussed on the exploration of the close coupling between specific ITes and ITas while addressing common issues of 3D interactions. We specifically focused on the stages of interaction within Basic Interaction Tasks (BITas) i.e., data input, manipulation, navigation and selection. Common limitations of these tasks are: (1) the complexity of mapping generation for input devices, (2) fatigue in mid-air object manipulation, (3) space constraints in VR navigation; and (4) low accuracy in 3D mid-air selection. Along with two chapters of introduction and background, this thesis presents five main works. Chapter 3 focusses on the design of mid-air gesture mappings based on human tacit knowledge. Chapter 4 presents a solution to address user fatigue in mid-air object manipulation. Chapter 5 is focused on addressing space limitations in VR navigation. Chapter 6 describes an analysis and a correction method to address Drift effects involved in scale-adaptive VR navigation; and Chapter 7 presents a hybrid technique 3D/2D that allows for precise selection of virtual objects in highly dense environments (e.g., point clouds). Finally, we conclude discussing how the contributions obtained from this exploration, provide techniques and guidelines to design more natural 3DUIs

    Ideologies of computer scientists and technologists (Correctness beyond reason)

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    Ideologies of computer scientists and technologist

    The Image of Redemption in Literature, Media, and Society: 2018 SASSI Conference Proceedings

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    Conference proceedings of the 2018 meeting of the Society for the Academic Study of Social Imagery (SASSI). Selected, refereed essays on the conference theme of The Image of REDEMPTION in Literature, Media, and Society

    Functional space-time properties of team synergies in high-performance football

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    This thesis aimed to investigate the performance of high-level teams in football, through the analysis of the interactions of their players in the context of the game, as these interactions result in functional effects that could not otherwise be achieved (synergies). From a spatial point of view, we argue that the understanding of collective “payoffs” emerging from players’ interactions and their behavioural patterns, can be accomplished through ”Delaunay triangulations” and consequent ”Voronoi diagrams”. Analysing the positional data (22 players and the ball) in 20 games of the French premier league, in this thesis we essentially sought to focus on territorial dominance as a variable that potentially captures the spatial affordances perceived by players. Whether from a collective global point of view or from a perspective of the local interactions that arise in the game landscape. Supported by the ecological dynamics and the synergism hypothesis, in this thesis we begin by demonstrating the existing connection between the territorial dominance of a team and the offensive effectiveness, as well as the absence of temporal overlap between the ball possession status and territorial dominance. Similarly, we also demonstrated that the space dominance of each player, which contributes to the territorial dominance of the team as a whole, is constrained by the team’s formation and the role assumed by each player in this collective framework. In order to understand the dynamics of interactions between players and the functional effects that come from it, we then focus on two tasks that are related to collective performance: the pass and the shot. Reflecting on the need to find methods that capture how the distribution of players on the pitch influences the functional degrees of freedom of a team as a whole and the passing opportunities that emerge from it. And, at the level of finishing situations, how the dominance of space can be included in the quantification of the value that each player assigns to occupy a certain place in the game landscape, and which is at the basis of their decision-making (shoot or pass the ball to another teammate possibly better ”positioned”). In sum, through the initial conceptual framework and the applied studies, we argue that the analysis of team performance should focus on the functional synergies that result from interactions between players. In this way, we demonstrate, through some examples, how the methods and conclusions taken from this thesis can be applied in practice by football coaches.Esta tese teve como objetivo investigar a performance de equipas de alto nível no futebol, através da análise das interações dos seus jogadores no contexto do jogo pois daí resultam efeitos funcionais que apenas são atingidos através dessas mesmas interações (sinergias). De um ponto de vista espacial, defendemos que o estudo glocal das interações entre os jogadores para a compreensão do rendimento coletivo, pode ser realizado através de “triangulações de Delaunay” e consequentes “diagramas de Voronoi”. Analisando os dados posicionais dos 22 jogadores e da bola, em 20 jogos da primeira liga francesa, nesta tese procurámos essencialmente nos focar sobre o domínio territorial enquanto variável que capta potencialmente as affordances espaciais percebidas pelos jogadores. Seja de um ponto de vista global coletivo, seja numa perspetiva das interações locais que surgem na paisagem de jogo. Suportados pela dinâmica ecológica e pela hipótese do sinergismo, nesta tese começamos por demonstrar a ligação existente entre o domínio territorial das equipas e a sua efetividade ofensiva, bem como a inexistência de uma sobreposição temporal entre a posse de bola e esse domínio. De igual forma, também demonstrámos que o domínio do espaço de cada jogador, que contribui para o domínio territorial da equipa no seu todo, é constrangido pelo sistema de jogo das equipas e pelo papel assumido por cada jogador neste referencial coletivo. No sentido de compreender a dinâmica das interações entre os jogadores e os efeitos funcionais que daí advêm, focamo-nos seguidamente em duas tarefas que estão relacionadas com a performance coletiva: o passe e o remate. Refletindo sobre a necessidade de encontrar métodos que captem de que forma a distribuição dos jogadores em campo influencia os graus de liberdade funcionais de uma equipa no seu todo e as oportunidades de passe que daí emergem. E, ao nível das situações de finalização, de que forma o domínio do espaço poderá ser incluído na quantificação do valor que cada jogador atribui a ocupar um determinador espaço na paisagem de jogo e que está na base da sua tomada de decisão (rematar ou passar a bola para outro colega eventualmente melhor “posicionado”). Em suma, através do enquadramento conceptual inicial e dos estudos aplicados, defendemos que o estudo da performance das equipas deverá se centrar nas sinergias funcionais que resultam das interações entre os jogadores. Desta forma, demonstramos, através de alguns exemplos, como é que os métodos e ilações retirados desta tese poderão ser aplicados na prática pelos treinadores de futebol

    Abstracting Multidimensional Concepts for Multilevel Decision Making in Multirobot Systems

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    Multirobot control architectures often require robotic tasks to be well defined before allocation. In complex missions, it is often difficult to decompose an objective into a set of well defined tasks; human operators generate a simplified representation based on experience and estimation. The result is a set of robot roles, which are not best suited to accomplishing those objectives. This thesis presents an alternative approach to generating multirobot control algorithms using task abstraction. By carefully analysing data recorded from similar systems a multidimensional and multilevel representation of the mission can be abstracted, which can be subsequently converted into a robotic controller. This work, which focuses on the control of a team of robots to play the complex game of football, is divided into three sections: In the first section we investigate the use of spatial structures in team games. Experimental results show that cooperative teams beat groups of individuals when competing for space and that controlling space is important in the game of robot football. In the second section, we generate a multilevel representation of robot football based on spatial structures measured in recorded matches. By differentiating between spatial configurations appearing in desirable and undesirable situations, we can abstract a strategy composed of the more desirable structures. In the third section, five partial strategies are generated, based on the abstracted structures, and a suitable controller is devised. A set of experiments shows the success of the method in reproducing those key structures in a multirobot system. Finally, we compile our methods into a formal architecture for task abstraction and control. The thesis concludes that generating multirobot control algorithms using task abstraction is appropriate for problems which are complex, weakly-defined, multilevel, dynamic, competitive, unpredictable, and which display emergent properties

    2019 Symposium Brochure

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    'The talent is out there' Talent development in Irish football: an examination of organizational structure and practice

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    Football is one of the most complex and competitive sports in which to reach elite levels (Haugaasen, Toering, & Jordet, 2014). Differences in sport systems, societal norms, cultural traditions, sociological and organisational issues may influence an athlete’s complex career development journey (Stambulova, 2009; Henriksen et al., 2010; Richardson, Relvas, & Littlewood, 2013). An ecological approach to development views child development within the context of a system of relationships that form his or her environment; therefore, to foster future positive behaviours and change developmental trajectories one must identify and understand direct and indirect influences on development (Bronfenbrenner, 1977; Gabbard & Krebs, 2012). The aim of this thesis was to examine the football governance landscape in the Republic of Ireland in relation to its ability to develop youth footballers, whilst exploring the contextual and lived experiences of these youth players as they developed within their respective talent development environments. This study employed a mixed method approach which involved quantitative and qualitative research data in a collection of studies. Study One, analysed and presented the demographics of those involved in the Football Association of Ireland’s primary talent development mechanism (n=1936), the Emerging Talent Programme (ETP). This study found a significant Relative Age Effect (RAE) and inequity of access to the ETP in relation to place of birth within the cohort. It also identified clear patterns of internal migration, with footballers moving towards the ‘core’ footballing development centre of Ireland (Dublin District Schoolboy League, DDSL). Study Two assessed the talent development practices of all authoritative bodies within Irish youth football with respect to organisational, governance, athletic, psycho-social, cultural and environmental issues. This study identified tensions and incongruence between strategic apex organisations resulting from Governing Body leadership, board composition, political dominance and perceptions of a lack of organisational justice. Structural and resource inequalities were identified in relation to finance, scouting networks, quality of coaching, facilities and player volume. Such incongruence combined with inequalities, led to concerns regarding youth development. Study Three provided a lived experience insight into the talent development pathway encountered by Irish footballers. This study followed five footballers who were on the Republic of Ireland under 15 international team, for a period of four years. This journey provided an insight into the impact that macro factors (identified in Study One and Study Two) had on the experiences of a developing footballer. Overall the thesis has provided an original contribution to the study of talent development in Irish football, providing a holistic analysis of the development pathway, its governance structures and the resulting lived experience of the pathway, utilising a bio-ecological approach

    WiFi-Based Human Activity Recognition Using Attention-Based BiLSTM

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    Recently, significant efforts have been made to explore human activity recognition (HAR) techniques that use information gathered by existing indoor wireless infrastructures through WiFi signals without demanding the monitored subject to carry a dedicated device. The key intuition is that different activities introduce different multi-paths in WiFi signals and generate different patterns in the time series of channel state information (CSI). In this paper, we propose and evaluate a full pipeline for a CSI-based human activity recognition framework for 12 activities in three different spatial environments using two deep learning models: ABiLSTM and CNN-ABiLSTM. Evaluation experiments have demonstrated that the proposed models outperform state-of-the-art models. Also, the experiments show that the proposed models can be applied to other environments with different configurations, albeit with some caveats. The proposed ABiLSTM model achieves an overall accuracy of 94.03%, 91.96%, and 92.59% across the 3 target environments. While the proposed CNN-ABiLSTM model reaches an accuracy of 98.54%, 94.25% and 95.09% across those same environments
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