In this paper, we present 'Virtual Observation' (VO) a software tool for contextual observation and assessment of user's directly from within the virtual reality (VR) simulation framework. Unlike other recording systems, the VO system described in this paper focuses on recording and reconstructing VR user's positional, rotational and input data to recreate the same experience the user had with a VR simulation. Different from animation-based approaches, VO records user inputs and reconstructs the simulation from them and the user positional data. Moreover, the system allows the broadcast of this information to a remote machine enabling remote live observation of the simulation. Datasets recorded by the system can be shared by exporting them as XML files or, optionally, into a standalone online application, such as browser WebGL, allowing researchers, developers and educators to share and review a VR user simulation through a free-moving camera using a web browser. In this paper, the consistency of the data generated from the software by the client, server and reconstructed datasets acquired during real-time live observations was evaluated. We conclude that this Virtual Observation software offers detailed reconstruction of low-level information and visual information of user actions during simulations for both live and offline observations. We envision that our system will be of benefit for researchers, developers and educators that work with VR applications.

Unlike conventional desktop simulations which have constrained interaction, immersive Virtual Reality (VR) allows users to freely move and interact with objects. In this paper we discuss a work-inprogress system that 'virtually' records participants movement and actions within a simulation. This system recovers and rebuilds recorded data on request, accurately replaying individual participants motions and actions in the simulation. Observers can review this reconstruction using an unrestricted virtual camera and if necessary, observe changes from recorded input devices. Reconstruction of each participants' skeleton structure was created using tracked input devices. We conclude that our system offers detailed recreation of high-level knowledge and visual information of participant actions during simulations.

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Professional video recording is a complex process which often requires expensive cameras and large amounts of ancillary equipment. With the advancement of mobile technologies, cameras on mobile devices have improved to the point where the quality of their output is sometimes comparable to that obtained from a professional video camera and are often used in professional productions. However, tools that allow professional users to access the information they need to control the technical quality of their filming and make an informed decision about what they are recording are missing on mobile platforms. In this paper we present MAVIS (Mobile Acquisition and VISualization) a tool for professional filming on a mobile platform. MAVIS allows users to access information such as colour vectorscope, waveform monitor, false colouring, focus peaking and all other information that is needed to produce high quality professional videos. This is achieved by exploiting the capabilities of modern mobile GPUs though the use of a number of vertex and fragment shaders. Evaluation with professionals in the film industry shows that the app and its functionalities are well received and that the output and usability of the application align with professional standards.

This paper validates an approach to the design and development of VR applications that are integrated into the curricula and address fundamental student needs. To accomplish this, a case study describing the process undertaken to create Nursing XR, a wound dressing scenario where the patient is discharged home and requires follow up care and treatment by a nurse. The aim of the VR application is to support nursing students in developing their communication, risk assessment, holistic assessment, and person-centred clinical decision-making skills. To design Nursing XR, needs and initial requirements were collected via a workshop with student nurses. The workshop, which involved 10 student nurses and two lecturers in nursing from two Universities (Co-Is) and was led by the PI, supported by the learning technologist and the head developer of the company used for development of the software. Results from the workshop identified two major needs for the students: the need to undertake practical applications of the procedures learned in the lectures and the need to build confidence in the skills required of a nursing student. These needs were the foundations for the design process, which followed an artefact-based approach. The artefacts generated during the design were also used to elicit additional interaction and software requirements from the nursing lecturers. An iterative lean development process was followed by the company for the software implementation. Throughout the development, students and lecturers were involved as user testes ensuring that the user experience of the application was satisfactory, and the application fit for purpose.In this paper, we describe the high-level design and development process followed by the multidisciplinary team to develop Nursing XR and report initial qualitative findings from the workshop focus group.