Humans ignore motion and stereo cues in favor of a fictional stable world

As we move through the world, our eyes acquire a sequence of images. The information from this sequence is sufficient to determine the structure of a three-dimensional scene, up to a scale factor determined by the distance that the eyes have moved [1, 2]. Previous evidence shows that the human visual system accounts for the distance the observer has walked [3,4] and the separation of the eyes [5-8] when judging the scale, shape, and distance of objects. However, in an immersive virtual-reality environment, observers failed to notice when a scene expanded or contracted, despite having consistent information about scale from both distance walked and binocular vision. This failure led to large errors in judging the size of objects. The pattern of errors cannot be explained by assuming a visual reconstruction of the scene with an incorrect estimate of interocular separation or distance walked. Instead, it is consistent with a Bayesian model of cue integration in which the efficacy of motion and disparity cues is greater at near viewing distances. Our results imply that observers are more willing to adjust their estimate of interocular separation or distance walked than to accept that the scene has changed in size.

Quantitative analysis of accuracy of an inertial/acoustic 6DOF tracking system in motion

An increasing number of neuroscience experiments are using virtual reality to provide a more immersive and less artificial experimental environment. This is particularly useful to navigation and three-dimensional scene perception experiments. Such experiments require accurate real-time tracking of the observer's head in order to render the virtual scene. Here, we present data on the accuracy of a commonly used six degrees of freedom tracker (Intersense IS900) when it is moved in ways typical of virtual reality applications. We compared the reported location of the tracker with its location computed by an optical tracking method. When the tracker was stationary, the root mean square error in spatial accuracy was 0.64 mm. However, we found that errors increased over ten-fold (up to 17 mm) when the tracker moved at speeds common in virtual reality applications. We demonstrate that the errors we report here are predominantly due to inaccuracies of the IS900 system rather than the optical tracking against which it was compared. (c) 2006 Elsevier B.V. All rights reserved.

Case Study: Interacting with Volumetric Medical Datasets in Networked CAVE Environments

Virtual Reality (VR) is widely used in visualizing medical datasets. This interest has emerged due to the usefulness of its techniques and features. Such features include immersion, collaboration, and interactivity. In a medical visualization context, immersion is important, because it allows users to interact directly and closelywith detailed structures in medical datasets. Collaboration on the other hand is beneficial, because it gives medical practitioners the chance to share their expertise and offer feedback and advice in a more effective and intuitive approach. Interactivity is crucial in medical visualization and simulation systems, because responsiveand instantaneous actions are key attributes in applications, such as surgical simulations. In this paper we present a case study that investigates the use of VR in a collaborative networked CAVE environment from a medical volumetric visualization perspective. The study will present a networked CAVE application, which has been built to visualize and interact with volumetric datasets. We will summarize the advantages of such an application and the potential benefits of our system. We also will describe the aspects related to this application area and the relevant issues of such implementations.

Human-machine symbiosis overview

The interface between humans and technology is a rapidly changing field. In particular as technological methods have improved dramatically so interaction has become possible that could only be speculated about even a decade earlier. This interaction can though take on a wide range of forms. Indeed standard buttons and dials with televisual feedback are perhaps a common example. But now virtual reality systems, wearable computers and most of all, implant technology are throwing up a completely new concept, namely a symbiosis of human and machine. No longer is it sensible simply to consider how a human interacts with a machine, but rather how the human-machine symbiotic combination interacts with the outside world. In this paper we take a look at some of the recent approaches, putting implant technology in context. We also consider some specific practical examples which may well alter the way we look at this symbiosis in the future. The main area of interest as far as symbiotic studies are concerned is clearly the use of implant technology, particularly where a connection is made between technology and the human brain and/or nervous system. Often pilot tests and experimentation has been carried out apriori to investigate the eventual possibilities before human subjects are themselves involved. Some of the more pertinent animal studies are discussed briefly here. The paper however concentrates on human experimentation, in particular that carried out by the authors themselves, firstly to indicate what possibilities exist as of now with available technology, but perhaps more importantly to also show what might be possible with such technology in the future and how this may well have extensive social effects. The driving force behind the integration of technology with humans on a neural level has historically been to restore lost functionality in individuals who have suffered neurological trauma such as spinal cord damage, or who suffer from a debilitating disease such as lateral amyotrophic sclerosis. Very few would argue against the development of implants to enable such people to control their environment, or some aspect of their own body functions. Indeed this technology in the short term has applications for amelioration of symptoms for the physically impaired, such as alternative senses being bestowed on a blind or deaf individual. However the issue becomes distinctly more complex when it is proposed that such technology be used on those with no medical need, but instead who wish to enhance and augment their own bodies, particularly in terms of their mental attributes. These issues are discussed here in the light of practical experimental test results and their ethical consequences.

Low-cost optical tracking for immersive collaboration in the CAVE using the Wii remote

We present a novel way of interacting with an immersive virtual environment which involves inexpensive motion-capture using the Wii Remote®. A software framework is also presented to visualize and share this information across two remote CAVETM-like environments. The resulting applications can be used to assist rehabilitation by sending motion information across remote sites. The application’s software and hardware components are scalable enough to be used on desktop computer when home-based rehabilitation is preferred.

Visual eye disease simulator

Visually impaired people have a very different view of the world such that seemingly simple environments as viewed by a ‘normally’ sighted people can be difficult for people with visual impairments to access and move around. This is a problem that can be hard to fully comprehend by people with ‘normal vision’ even when guidelines for inclusive design are available. This paper investigates ways in which image processing techniques can be used to simulate the characteristics of a number of common visual impairments in order to provide, planners, designers and architects, with a visual representation of how people with visual impairments view their environment, thereby promoting greater understanding of the issues, the creation of more accessible buildings and public spaces and increased accessibility for visually impaired people in everyday situations.

Immersive open surgery simulation

Realistic medical simulation has great potential for augmenting or complimenting traditional medical training or surgery planning, and Virtual Reality (VR) is a key enabling technology for delivering this goal. Although, medical simulators are now widely used in medical institutions, the majority of them are still reliant on desktop monitor displays, and many are restricted in their modelling capability to minimally invasive or endoscopic surgery scenarios. Whilst useful, such models lack the realism and interaction of the operating theatre. In this paper, we describe how we are advancing the technology by simulating open surgery procedures in an Immersive Projection Display CAVE environment thereby enabling medical practitioners to interact with their virtual patients in a more realistic manner.

Immersive co-operative psychological virtual environments (ICPVE)

Virtual Reality (VR) has been used in a variety of forms to assist in the treatment of a wide range of psychological illness. VR can also fulfil the need that psychologists have for safe environments in which to conduct experiments. Currently the main barrier against using this technology is the complexity in developing applications. This paper presents two different co-operative psychological applications which have been developed using a single framework. These applications require different levels of co-operation between the users and clients, ranging from full psychologist involvement to their minimal intervention. This paper will also discuss our approach to developing these different environments and our experiences to date in utilising these environments.

Addressing animal health knowledge gaps in Southern Countries: the creation of a 2D animal health resource room

Livestock are a key asset for the global poor. However, access to relevant information is a critical issue for both livestock development practitioners and the poor themselves. Therefore, the following paper details the creation of an on-line Animal Health Resource Room. The aim was to create an immersive environment, which mimics the benefits of a 3D Virtual Learning Environment without the constraints on download times. Therefore, in the following paper key issues in the dissemination of such a platform such as connectivity and speed are explored within the wider context of the development of the tool itself.

Integrating augmented reality with home systems

Augmented Reality systems overlay computer generated information onto a user's natural senses. Where this additional information is visual, the information is overlaid on the user's natural visual field of view through a head mounted (or “head-up”) display device. Integrated Home Systems provides a network that links every electrical device in the home which provides to a user both control and data transparency across the network.

Evoked prior learning experience and approach to learning as predictors of academic achievement

Background. In separate studies and research from different perspectives, five factors are found to be among those related to higher quality outcomes of student learning (academic achievement). Those factors are higher self-efficacy, deeper approaches to learning, higher quality teaching, students’ perceptions that their workload is appropriate, and greater learning motivation. University learning improvement strategies have been built on these research results. Aim. To investigate how students’ evoked prior experience, perceptions of their learning environment, and their approaches to learning collectively contribute to academic achievement. This is the first study to investigate motivation and self-efficacy in the same educational context as conceptions of learning, approaches to learning and perceptions of the learning environment. Sample. Undergraduate students (773) from the full range of disciplines were part of a group of over 2,300 students who volunteered to complete a survey of their learning experience. On completing their degrees 6 and 18 months later, their academic achievement was matched with their learning experience survey data. Method. A 77-item questionnaire was used to gather students’ self-report of their evoked prior experience (self-efficacy, learning motivation, and conceptions of learning), perceptions of learning context (teaching quality and appropriate workload), and approaches to learning (deep and surface). Academic achievement was measured using the English honours degree classification system. Analyses were conducted using correlational and multi-variable (structural equation modelling) methods. Results. The results from the correlation methods confirmed those found in numerous earlier studies. The results from the multi-variable analyses indicated that surface approach to learning was the strongest predictor of academic achievement, with self-efficacy and motivation also found to be directly related. In contrast to the correlation results, a deep approach to learning was not related to academic achievement, and teaching quality and conceptions of learning were only indirectly related to achievement. Conclusions. Research aimed at understanding how students experience their learning environment and how that experience relates to the quality of their learning needs to be conducted using a wider range of variables and more sophisticated analytical methods. In this study of one context, some of the relations found in earlier bivariate studies, and on which learning intervention strategies have been built, are not confirmed when more holistic teaching–learning contexts are analysed using multi-variable methods.

Modelling human visual navigation using multi-view scene reconstruction

It is often assumed that humans generate a 3D reconstruction of the environment, either in egocentric or world-based coordinates, but the steps involved are unknown. Here, we propose two reconstruction-based models, evaluated using data from two tasks in immersive virtual reality. We model the observer’s prediction of landmark location based on standard photogrammetric methods and then combine location predictions to compute likelihood maps of navigation behaviour. In one model, each scene point is treated independently in the reconstruction; in the other, the pertinent variable is the spatial relationship between pairs of points. Participants viewed a simple environment from one location, were transported (virtually) to another part of the scene and were asked to navigate back. Error distributions varied substantially with changes in scene layout; we compared these directly with the likelihood maps to quantify the success of the models. We also measured error distributions when participants manipulated the location of a landmark to match the preceding interval, providing a direct test of the landmark-location stage of the navigation models. Models such as this, which start with scenes and end with a probabilistic prediction of behaviour, are likely to be increasingly useful for understanding 3D vision.