Development and Specification of Virtual Environments

This thesis concerns the issues involved in the development of virtual environments (VEs). VEs are more than virtual reality. We identify four main characteristics of them: graphical interaction, multimodality, interface agents, and multi-user. These characteristics are illustrated with an overview of different classes of VE-like applications, and a number of state-of-the-art VEs. To further define the topic of research, we propose a general framework for VE systems development, in which we identify five major classes of development tools: methodology, guidelines, design specification, analysis, and development environments. Of each, we give an overview of existing best practices

Automated specification-based testing of graphical user interfaces

Tese de doutoramento. Engenharia Electrónica e de Computadores. 2006. Faculdade de Engenharia. Universidade do Porto, Departamento de Informática, Escola de Engenharia. Universidade do Minh

Proceedings of the 1st joint workshop on Smart Connected and Wearable Things 2016

These are the Proceedings of the 1st joint workshop on Smart Connected and Wearable Things (SCWT'2016, Co-located with IUI 2016). The SCWT workshop integrates the SmartObjects and IoWT workshops. It focusses on the advanced interactions with smart objects in the context of the Internet-of-Things (IoT), and on the increasing popularity of wearables as advanced means to facilitate such interactions

Using the PAC-Amodeus Model and Design Patterns to Make Interactive an Existing Object-Oriented Kernel

International audienceThis paper presents an efficient way to provide a graphical interactive visualisation to a noninteractive existing object oriented application. Assuming that the initial application uses an ‘Abstract Factory' pattern (GoF87) in order to create new objects, our aim is achieved by using the PAC-Amodeus model and extending the existing objects to create intermediate components, using object oriented techniques: inheritance, polymorphism and dynamic binding, using the ‘Proxy' pattern (GoF207). Although our field of interest is physical and behavioural simulation, the techniques developed in this paper can be applied to any non–interactive object oriented existing kernel. Then, we present a complete simulation example ‘Bugs life' to illustrate the use of our method. Finally, we point out the limits of our approach, and we suggest new directions for further work

Audio-coupled video content understanding of unconstrained video sequences

Unconstrained video understanding is a difficult task. The main aim of this thesis is to recognise the nature of objects, activities and environment in a given video clip using both audio and video information. Traditionally, audio and video information has not been applied together for solving such complex task, and for the first time we propose, develop, implement and test a new framework of multi-modal (audio and video) data analysis for context understanding and labelling of unconstrained videos. The framework relies on feature selection techniques and introduces a novel algorithm (PCFS) that is faster than the well-established SFFS algorithm. We use the framework for studying the benefits of combining audio and video information in a number of different problems. We begin by developing two independent content recognition modules. The first one is based on image sequence analysis alone, and uses a range of colour, shape, texture and statistical features from image regions with a trained classifier to recognise the identity of objects, activities and environment present. The second module uses audio information only, and recognises activities and environment. Both of these approaches are preceded by detailed pre-processing to ensure that correct video segments containing both audio and video content are present, and that the developed system can be made robust to changes in camera movement, illumination, random object behaviour etc. For both audio and video analysis, we use a hierarchical approach of multi-stage classification such that difficult classification tasks can be decomposed into simpler and smaller tasks. When combining both modalities, we compare fusion techniques at different levels of integration and propose a novel algorithm that combines advantages of both feature and decision-level fusion. The analysis is evaluated on a large amount of test data comprising unconstrained videos collected for this work. We finally, propose a decision correction algorithm which shows that further steps towards combining multi-modal classification information effectively with semantic knowledge generates the best possible results

Towards exploring future landscapes using augmented reality

With increasing pressure to better manage the environment many government and private organisations are studying the relationships between social, economic and environmental factors to determine how they can best be optimised for increased sustainability. The analysis of such relationships are undertaken using computer-based Integrated Catchment Models (ICM). These models are capable of generating multiple scenarios depicting alternative land use alternatives at a variety of temporal and spatial scales, which present (potentially) better Triple-Bottom Line (TBL) outcomes than the prevailing situation. Dissemination of this data is (for the most part) reliant on traditional, static map products however, the ability of such products to display the complexity and temporal aspects is limited and ultimately undervalues both the knowledge incorporated in the models and the capacity of stakeholders to disseminate the complexities through other means. Geovisualization provides tools and methods for disseminating large volumes of spatial (and associated non-spatial) data. Virtual Environments (VE) have been utilised for various aspects of landscape planning for more than a decade. While such systems are capable of visualizing large volumes of data at ever-increasing levels of realism, they restrict the users ability to accurately perceive the (virtual) space. Augmented Reality (AR) is a visualization technique which allows users freedom to explore a physical space and have that space augmented with additional, spatially referenced information. A review of existing mobile AR systems forms the basis of this research. A theoretical mobile outdoor AR system using Common-Of-The-Shelf (COTS) hardware and open-source software is developed. The specific requirements for visualizing land use scenarios in a mobile AR system were derived using a usability engineering approach known as Scenario-Based Design (SBD). This determined the elements required in the user interfaces resulting in the development of a low-fidelity, computer-based prototype. The prototype user interfaces were evaluated using participants from two targeted stakeholder groups undertaking hypothetical use scenarios. Feedback from participants was collected using the cognitive walk-through technique and supplemented by evaluator observations of participants physical actions. Results from this research suggest that the prototype user interfaces did provide the necessary functionality for interacting with land use scenarios. While there were some concerns about the potential implementation of "yet another" system, participants were able to envisage the benefits of visualizing land use scenario data in the physical environment

ETAG, A Formal Model of Competence Knowledge for User Interface Design

Vliet, J.C. van [Promotor]Tauber, M.J. [Copromotor]Veer, G.C. van der [Copromotor

Audio-coupled video content understanding of unconstrained video sequences

Unconstrained video understanding is a difficult task. The main aim of this thesis is to recognise the nature of objects, activities and environment in a given video clip using both audio and video information. Traditionally, audio and video information has not been applied together for solving such complex task, and for the first time we propose, develop, implement and test a new framework of multi-modal (audio and video) data analysis for context understanding and labelling of unconstrained videos. The framework relies on feature selection techniques and introduces a novel algorithm (PCFS) that is faster than the well-established SFFS algorithm. We use the framework for studying the benefits of combining audio and video information in a number of different problems. We begin by developing two independent content recognition modules. The first one is based on image sequence analysis alone, and uses a range of colour, shape, texture and statistical features from image regions with a trained classifier to recognise the identity of objects, activities and environment present. The second module uses audio information only, and recognises activities and environment. Both of these approaches are preceded by detailed pre-processing to ensure that correct video segments containing both audio and video content are present, and that the developed system can be made robust to changes in camera movement, illumination, random object behaviour etc. For both audio and video analysis, we use a hierarchical approach of multi-stage classification such that difficult classification tasks can be decomposed into simpler and smaller tasks. When combining both modalities, we compare fusion techniques at different levels of integration and propose a novel algorithm that combines advantages of both feature and decision-level fusion. The analysis is evaluated on a large amount of test data comprising unconstrained videos collected for this work. We finally, propose a decision correction algorithm which shows that further steps towards combining multi-modal classification information effectively with semantic knowledge generates the best possible results.EThOS - Electronic Theses Online ServiceGBUnited Kingdo