Competitive VR gaming has emerged as a new trend in recent years, due to the availability of consumer grade VR technologies and the rise of esports as a billion dollar industry. Despite the considerable attention to competitive VR gaming, there is a lack of research on attitudes and experiences that players have with these games. In this qualitative study with a pre-post interview design, we recruited eight competitive Counter-Strike: Global Offensive players from a university esports club. We aimed to understand their attitudes towards VR esports and their experiences playing a representative location based VR esports game. Findings showed that players had visceral and positive affective experiences in the game, such as how players map physical movements to the game. These findings can help design future competitive VR esports, while also further contributing to HCI as the first exploration on player experiences with VR esports, laying groundwork for future studies.

As head mounted displays and 360° video cameras are becoming affordable, they offer opportunities to personalise immersive learning experiences to local contexts and individuals. In this paper, we present lessons learnt from a participatory design process focused on understanding engagement and preferences of users with intellectual disability viewing 360° videos. Over 4 iterations involving re-designs informed by interviews and observations of two to four participants with intellectual disability, we have established that: participants are more comfortable with using the technology if they are first introduced to a familiar scene before seeing anything new, they prefer to be 'accompanied' by an in-video facilitator, and participants engage more with the immersive visual environment when prompted to look around from within the video. We have also established a number of guidelines for filming with a 360° camera with regards to movement and viewpoint.

Identifying, modelling and documenting business processes requires the collaboration of many stakeholders that may be spread across companies in inter-organizational business settings. While there are many process modelling tools available, the support they provide for remote collaboration remains limited. This paper investigates the application of virtual environment and augmented reality technologies to remote process modelling, with the aim to assisting collaboration tasks by providing an increased sense of immersion in a shared workspace. We report on the evaluation of a prototype system with five informants. The results indicate that this approach to business process modelling is suited to remote collaborative task settings, and stakeholders may indeed benefit from using augmented reality interfaces.

Much research on 3D graphics collaboration has focused on improving collaborative viewing or enabling simple manipulations. There are, however, two major problems which are not yet resolved in collaborative environments. Simultaneous manipulation of a common 3D object by users can cause conflicts, and the integrity of the source 3D object will be compromised during updates. 3D objects can be locked for exclusive use to prevent conflicts, but this requires users to wait for their turn in order to perform manipulations. The capability of seamless and simultaneous manipulation raises several challenges such as how to resolve manipulation conflict and to deliver manipulation commands to users.

Information uncertainty is inherent in many problems and is often subtle and complicated to understand. Although visualization is a powerful means for exploring and understanding information, information uncertainty visualization is ad hoc and not widespread. This paper identifies two main barriers to the uptake of information uncertainty visualization: firstly, the difficulty of modeling and propagating the uncertainty information; and secondly, the difficulty of mapping uncertainty to visual elements. To overcome these barriers, we extend the spreadsheet paradigm to encapsulate uncertainty details within cells. This creates an inherent awareness of the uncertainty associated with each variable. The spreadsheet can hide the uncertainty details, enabling the user to think simply in terms of variables. Furthermore, the system can aid with automated propagation of uncertainty information, since it is intrinsically aware of the uncertainty. The system also enables mapping the encapsulated uncertainty to visual elements via the formula language and a visualization sheet. Support for such low-level visual mapping provides flexibility to explore new techniques for information uncertainty visualization.

For some time now, image retrieval approaches have been developed that use low-level features, such as colour histograms, edge distributions and texture measures. What has been lacking in image retrieval approaches is the development of general methods for more structured object recognition. This paper describes in detail a general hierarchical image classifier approach, and illustrates the ease with which it can be trained to find objects in a scene. To further illustrate the wide capabilities of this approach, results from its application to particle picking in biology and Vietnamese art image retrieval are listed.

Present fuzzy system visualisations while being useful, have been ad hoc in nature. In this paper we present a new integrated task-oriented approach to the visualisation of fuzzy logic systems. In addition, this approach is incorporated into an agent-based software architecture to guide the user through the process of developing a fuzzy logic system visualisation. A case study then illustrates a structured walk through of the new approach with an electricity spot price prediction application.

Experiments have shown that viewers only regard certain informative regions within a presented image. Furthermore, it has been shown that these regions of interest contain low level feature differences that influence the fixation time of the viewer. We present a fuzzy logic model of visual attention which seeks to compute the relative visual importance of regions in an image based upon these spatial feature differences. We also demonstrate some of the possible savings to be had in applying the visual importance model to the modulation of super-sampling In a ray-traced image. We expect this approach to have applications in the entertainment industry where image fidelity may be sacrificed for efficiency purposes.