This study explores the psychological and physiological health benefits of virtual environments, particularly comparing the effects of a virtual meadow to the absence of a virtual environment to explore the effectiveness of VR as a stress relief. Given the increasing urbanisation and limited access to natural settings, this research investigates whether virtual realities can serve as a feasible alternative for enhancing mental health. The study hypothesis is that exposure to an interactive Meadow Forest virtual environment, not only facilitates stress relief but also provides short-term residual calming effects. Employing a mixed-methods approach, the study integrates bio-metric data, the Self-Assessment Manikin, and structured interviews to evaluate the emotional and physical responses of participants before and after exposure to a virtual green space. Although results indicate that virtual environments can reduce stress levels immediately after exposure, they do not significantly lower stress below baseline levels nor provide lasting residual benefits. This paper discusses the implications of these findings for future virtual reality applications in therapeutic contexts and highlights the need for more comprehensive studies to establish the potential long-term benefits of virtual environments in mental health practices.

Pretend play is a stage in early childhood development where children learn and develop language and social skills through acting out imaginary scenarios. Pretend play skills are typically delayed for children with Autism Spectrum Disorders (ASD). Digital technology has been successfully used to engage children with ASD in pretend play, however research around the needs and requirements of the user is often omitted in these designs. Human Centered Design (HCD) provides a way of including these needs and making interventions suitably accessible to the target user. This paper presents the results of a multi-stage HCD process including observations, interviews and a Delphi study, using both the primary group (children with ASD) and their proxies (professionals who work closely with the group). The final result is a set of User Requirements which emerged from the data in the HCD stages. The User Requirements and guidelines presented provide researchers with a tool for developing digital pretend play interventions for children with ASD. Future research could benefit by incorporating the User Requirements when designing digital pretend play interventions, which is a small but growing area of research.

In this paper, we introduce a novel methodology for the optimization of photogrammetry data of physical objects for use in metaverse virtual environments. Our approach focuses on an artist-driven process to optimize mesh and textures derived from photogrammetry, ensuring authentic and accurate recreation of real-world objects for low-powered VR devices. By leveraging this methodology, we aim to enhance the user experience in virtual environments by providing realistic and immersive representations of physical objects while maintaining optimal performance on a wide range of devices. This paper details the development and implementation of our methodology, as well as its potential applications and benefits in the rapidly evolving metaverse landscape.

The human visual and auditory systems are attentive to variations in both lighting and sound, and changes in either are used in audiovisual media to draw attention. In video games specifically, many embedded navigational cues are utilised to subtly suggest navigational choices to players. Both lighting and audio cues are commonly utilised by game designers to signal specific events or to draw player focus and therefore influence navigational decisions. We analyse the influence that combinations of landmark, auditory and illumination cues have on player navigation. 134 participants navigated through a randomly assigned subset of thirty structurally similar virtual mazes with variations of lighting, spatial audio and landmark cues. The solve times for these mazes were analysed to determine the influence of each individual cue and evaluate any cue competition or interactions effects detected. The findings demonstrate that auditory and subtle lighting had distinct effects on navigation and maze solve times and that interactions and cue competition effects were also evident.

For almost 120 years, it has been demonstrated in literature that humans are susceptible to many different types of change blindness; essentially if a change in a visual scene is not sudden or obvious, it fails to be detected. Research utilising video game environments provides the opportunity for the study of change blindness during dynamic and interactive tasks. This study examined participant perception of gradual broad changes to both colour and textural information across surfaces and objects in a video game mimicking that of a First-Person adventure or point and click game/genre escape room task. 119 participants were asked to solve a room escape puzzle, results demonstrated that perception of gradual textural changes to an environment across a range of decreasing durations (90 s, 45 s, 22.5 s & 11.25 s) were detected only by a very small proportion of participants (4.20%). There was no significant effect of the variation in time on detection rates.

A novel framework is introduced to handle the pedestrian detection in mid-high crowd density. This framework exploits the samples obtained with the unsupervised approach, extracts the combined pattern of Histograms of Oriented Gradients (HOG) and Local Binary Pattern (LBP) for the training and detection. The motion information is utilized to adjust the confidence score of detect annotation, and the soft-NMS is used to handle the balance between the removing of redundant annotation and occlusion. The experiments indicate the proposed approach achieved a promising result compared to state-of-the-art trained with the benchmarking dataset.

Having taught home, European Union (EU) and international students in Higher Education (HE) over a range of Games and Web courses for a combined total of 50 years, the authors have been consistently impressed with the ambition and achievements of their EU students. In this chapter, research relating to student relocation and internationalisation are assessed with reference to the EU and, in particular, former Eastern-bloc countries. Theoretical benefits of study in the UK are researched and indicate that EU students' home country's second language is English; that an English study language is preferred; UK universities are seen as world-competing institutions; software for this sector is largely produced by English-speaking nations (USA and UK); programming languages were developed in English; and finance implications (the rise of tuition fees) haven't put off the ambitious and high-attaining applicants. Graduate feedback confirms the desire to work in an English-speaking environment for maximum employability, the global stage being open to them via a UK degree. Our degrees are seen as commanding high value and respect worldwide and opening up employment opportunities by rising above any perceived home-country barriers. Our EU students report having researched the University and course extensively before choosing their study and many want to learn more and to be pushed harder and further. Negatively, they comment about the lack of ambition and motivation in some of their respective cohorts, many of which are home students. Their feedback confirms the authors' impression of EU students and provides many areas to improve the existing course offerings.

We undertake a usability evaluation of tablet computers and handwriting capture and recognition software for use in the classroom.The aim is to assess whether the current crop of tablets and available software offer a viable platform for the immediate capture and dissemination of formative or summative written feedback.If so, then these devices could offer an effective and efficient approach to sharing feedback with our students.We examine a range of tablet devices, covering the major operating systems and touchscreen technologies.For each device, we consider a selection of handwriting capture and recognition apps, in each case choosing the best available for a detailed usability analysis.We develop usability criteria based on Nielsen's Heuristics, refining them for the task at hand.The set of usability criteria developed should prove useful as a basis for future usability analyses of mobile technologies Our findings indicate that there are combinations of tablet computer and handwriting capture, or recognition, software available now that are suitable for use in the classroom.The better quality combinations can be used for capturing and disseminating both formative and summative feedback.Handwriting recognition does require a tablet with an active digitizer and good quality commercial software.Tablets with a good capacitive screen and high quality handwriting capture apps are an acceptable alternative if recognition is not required.

In this paper, we present a new approach for matching local descriptors such as Scale Invariant Feature Transform (SIFT) ones in order to recognize image objects quickly and reliably. The proposed method first computes the Hausdorff distance combined with the City-Block distance to match the two sets of the extracted keypoints from the goal and data images, respectively. Then, the matched points are involved into an embedded pairing process, leading to a double matching which is more discriminant for the object recognition purpose as demonstrated on real-world standard databases.

In order to develop a podiatric orthopaedic training simulator the obstacle of simulating podiatric bone surgery must be overcome. In order to simulate this surgery appropriately, it is necessary to be able to cut through a virtual representation of a patient’s foot on-screen in real-time. We investigate several methods of cutting through simulated objects in general, and evaluate their usefulness in simulating real-time interactive bone surgery. We determine that none of these conventional methods are fully suitable and instead propose, develop and test a method using planar slicing of polyhedral mesh geometry.

Over the last decade, visualization techniques for 3-dimensional volumetric models, especially those that can be performed on PC hardware platforms, have attracted intensive attention in the research communities. The rapid evolution on PC computers, specialist hardware, and even gaming consoles have accelerated this trend and seen the volume model-based applications being greatly extended from industrial design, medical simulation, to entertainment usage and beyond. As part of the effort, the interactive manipulation of the appearance of volume models, often referred as volume deformation, has become a research hots-pot due to its potentials in revealing the models' internal structures and material characteristics. This paper reports an innovative volume deformation method based on a self-extracting mechanism for the so-called “control lattice” from the “surface” of a volume model, which can then be applied on the entire model or a specifically segmented part of it based on user requirements. The detail level of the extracted control lattice can be customized based on Active Surface algorithms for ensuring the interactive rate and the final resolution for a particular application.

For the output of an augmented reality application to appear realistic a number of issues need to be taken into consideration. The illumination correspondence between the real and virtual components should be taken into account as well as the scene level of detail and the accuracy of alignment between the two worlds. This paper focuses on matching world illumination and photometric registration methods. It introduces a new technique that aims to utilize shadow/object interest point correspondences in order to locate and virtually reproduce real-life illuminants. The technique is attractive as it makes use of natural calibration objects in the form of natural scene geometry and associated shadows. Computational complexity is kept relatively low by using an interest point based approach. Further work to be undertaken is discussed.

Integrating virtual objects into real environments presents a number of technical and aesthetic challenges which limit the impressiveness of current augmented reality applications. Although some of these challenges have recently been addressed, others are still active areas of research. The quality of the models and textures used, accurate geometric world alignment and the quality of illumination correspondence all need to be considered. Literature shows the latter to be the least mature field and is the focus of this paper. This paper introduces a new photometric registration technique that makes use of image interest points. The technique attains illumination correspondence without the need for pre-calibration or unnatural calibration objects, instead natural image features such as shadow and object interest points are use. The operational complexity of the technique is low and real-time processing of live data is achieved. Current progress and future work are discussed in the paper.

A number of issues need to be taken into consideration for the output of an augmented reality application to appear realistic. Such issues include the level of detail of the virtual scene, the accuracy of alignment between the two worlds and the correspondence of illumination between the real and virtual components. This paper reviews geometric registration techniques that are commonly used to perform the alignment process and photometric registration techniques that match illumination conditions. A research project that investigates both geometric and photometric registration is discussed. Although a number of geometric registration techniques exist, feature based methods have not yet achieved popularity within production environments because of the associated difficulties. Instead, fiducial marker based systems are being implemented for their robustness and ease of implementation. Many photometric registration techniques require pre-calibration or extensive CPU time. Very few operate in real-time and are compatible with geometric techniques. Further work to be undertaken is discussed towards the end of the paper.

This paper reviews the recent progress in surface measurement methods using active vision and light-scattering techniques. The active vision methods with different structured light patterns and the corresponding techniques are summarized. The surface roughness and defects inspection with light-scattering are discussed. After the review, an integrative method to measure surface waviness and form, roughness is proposed.

Surface speckle pattern intensity distribution resulting from laser light scattering from a rough surface contains various information about the surface geometrical and physical properties. A surface roughness measurement technique based on the texture analysis of surface speckle pattern texture images is put forward. In the surface roughness measurement technique, the speckle pattern texture images are taken by a simple setup configuration consisting of a laser and a CCD camera. Our experimental results show that the surface roughness contained in the surface speckle pattern texture images has a good monotonic relationship with their energy feature of the gray-level co-occurrence matrices. After the measurement system is calibrated by a standard surface roughness specimen, the surface roughness of the object surface composed of the same material and machined by the same method as the standard specimen surface can be evaluated from a single speckle pattern texture image. The robustness of the characterization of speckle pattern texture for surface roughness is also discussed. Thus the surface roughness measurement technique can be used for an in-process surface measurement.

This paper presents a new approach for adaptive weighting schemes for multiple sensor fusion by using visualisation feedback control. A visualisation schema is used to coordinate the information content capture of different features from multiple sensors. The end-users can interact with the training sample distribution to obtain weights for the sensor data fusion and decision making. Based on the proposed fusion approach, some applications such as audiovisual biometric authentication and multi-modal surface measurement are discussed.