957 research outputs found

    Size and shape constancy in consumer virtual reality

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    With the increase in popularity of consumer virtual reality headsets, for research and other applications, it is important to understand the accuracy of 3D perception in VR. We investigated the perceptual accuracy of near-field virtual distances using a size and shape constancy task, in two commercially available devices. Participants wore either the HTC Vive or the Oculus Rift and adjusted the size of a virtual stimulus to match the geometric qualities (size and depth) of a physical stimulus they were able to refer to haptically. The judgments participants made allowed for an indirect measure of their perception of the egocentric, virtual distance to the stimuli. The data show under-constancy and are consistent with research from carefully calibrated psychophysical techniques. There was no difference in the degree of constancy found in the two headsets. We conclude that consumer virtual reality headsets provide a sufficiently high degree of accuracy in distance perception, to allow them to be used confidently in future experimental vision science, and other research applications in psychology

    Phenomenal regression as a potential metric of veridical perception in virtual environments

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    It is known that limitations of the visual presentation and sense of presence in a virtual environment (VE) can result in deficits of spatial perception such as the documented depth compression phenomena. Investigating size and distance percepts in a VE is an active area of research, where different groups have measured the deficit by employing skill-based tasks such as walking, throwing or simply judging sizes and distances. A psychological trait called phenomenal regression (PR), first identified in the 1930s by Thouless, offers a measure that does not rely on either judgement or skill. PR describes a systematic error made by subjects when asked to match the perspective projections of two stimuli displayed at different distances. Thouless’ work found that this error is not mediated by a subject’s prior knowledge of its existence, nor can it be consciously manipulated, since it measures an individual’s innate reaction to visual stimuli. Furthermore he demonstrated that, in the real world, PR is affected by the depth cues available for viewing a scene. When applied in a VE, PR therefore potentially offers a direct measure of perceptual veracity that is independent of participants’ skill in judging size or distance. Experimental work has been conducted and a statistically significant correlation of individuals’ measured PR values (their ‘Thouless ratio’, or TR) between virtual and physical stimuli was found. A further experiment manipulated focal depth to mitigate the mismatch that occurs between accommodation and vergence cues in a VE. The resulting statistically significant effect on TR demonstrates that it is sensitive to changes in viewing conditions in a VE. Both experiments demonstrate key properties of PR that contribute to establishing it as a robust indicator of VE quality. The first property is that TR exhibits temporal stability during the period of testing and the second is that it differs between individuals. This is advantageous as it yields empirical values that can be investigated using regression analysis. This work contributes to VE domains in which it is desirable to replicate an accurate perception of space, such as training and telepresence, where PR would be a useful tool for comparing subjective experience between a VE and the real world, or between different VEs

    Change blindness: eradication of gestalt strategies

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    Arrays of eight, texture-defined rectangles were used as stimuli in a one-shot change blindness (CB) task where there was a 50% chance that one rectangle would change orientation between two successive presentations separated by an interval. CB was eliminated by cueing the target rectangle in the first stimulus, reduced by cueing in the interval and unaffected by cueing in the second presentation. This supports the idea that a representation was formed that persisted through the interval before being 'overwritten' by the second presentation (Landman et al, 2003 Vision Research 43149–164]. Another possibility is that participants used some kind of grouping or Gestalt strategy. To test this we changed the spatial position of the rectangles in the second presentation by shifting them along imaginary spokes (by ±1 degree) emanating from the central fixation point. There was no significant difference seen in performance between this and the standard task [F(1,4)=2.565, p=0.185]. This may suggest two things: (i) Gestalt grouping is not used as a strategy in these tasks, and (ii) it gives further weight to the argument that objects may be stored and retrieved from a pre-attentional store during this task

    Spatial Interaction for Immersive Mixed-Reality Visualizations

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    Growing amounts of data, both in personal and professional settings, have caused an increased interest in data visualization and visual analytics. Especially for inherently three-dimensional data, immersive technologies such as virtual and augmented reality and advanced, natural interaction techniques have been shown to facilitate data analysis. Furthermore, in such use cases, the physical environment often plays an important role, both by directly influencing the data and by serving as context for the analysis. Therefore, there has been a trend to bring data visualization into new, immersive environments and to make use of the physical surroundings, leading to a surge in mixed-reality visualization research. One of the resulting challenges, however, is the design of user interaction for these often complex systems. In my thesis, I address this challenge by investigating interaction for immersive mixed-reality visualizations regarding three core research questions: 1) What are promising types of immersive mixed-reality visualizations, and how can advanced interaction concepts be applied to them? 2) How does spatial interaction benefit these visualizations and how should such interactions be designed? 3) How can spatial interaction in these immersive environments be analyzed and evaluated? To address the first question, I examine how various visualizations such as 3D node-link diagrams and volume visualizations can be adapted for immersive mixed-reality settings and how they stand to benefit from advanced interaction concepts. For the second question, I study how spatial interaction in particular can help to explore data in mixed reality. There, I look into spatial device interaction in comparison to touch input, the use of additional mobile devices as input controllers, and the potential of transparent interaction panels. Finally, to address the third question, I present my research on how user interaction in immersive mixed-reality environments can be analyzed directly in the original, real-world locations, and how this can provide new insights. Overall, with my research, I contribute interaction and visualization concepts, software prototypes, and findings from several user studies on how spatial interaction techniques can support the exploration of immersive mixed-reality visualizations.Zunehmende Datenmengen, sowohl im privaten als auch im beruflichen Umfeld, führen zu einem zunehmenden Interesse an Datenvisualisierung und visueller Analyse. Insbesondere bei inhärent dreidimensionalen Daten haben sich immersive Technologien wie Virtual und Augmented Reality sowie moderne, natürliche Interaktionstechniken als hilfreich für die Datenanalyse erwiesen. Darüber hinaus spielt in solchen Anwendungsfällen die physische Umgebung oft eine wichtige Rolle, da sie sowohl die Daten direkt beeinflusst als auch als Kontext für die Analyse dient. Daher gibt es einen Trend, die Datenvisualisierung in neue, immersive Umgebungen zu bringen und die physische Umgebung zu nutzen, was zu einem Anstieg der Forschung im Bereich Mixed-Reality-Visualisierung geführt hat. Eine der daraus resultierenden Herausforderungen ist jedoch die Gestaltung der Benutzerinteraktion für diese oft komplexen Systeme. In meiner Dissertation beschäftige ich mich mit dieser Herausforderung, indem ich die Interaktion für immersive Mixed-Reality-Visualisierungen im Hinblick auf drei zentrale Forschungsfragen untersuche: 1) Was sind vielversprechende Arten von immersiven Mixed-Reality-Visualisierungen, und wie können fortschrittliche Interaktionskonzepte auf sie angewendet werden? 2) Wie profitieren diese Visualisierungen von räumlicher Interaktion und wie sollten solche Interaktionen gestaltet werden? 3) Wie kann räumliche Interaktion in diesen immersiven Umgebungen analysiert und ausgewertet werden? Um die erste Frage zu beantworten, untersuche ich, wie verschiedene Visualisierungen wie 3D-Node-Link-Diagramme oder Volumenvisualisierungen für immersive Mixed-Reality-Umgebungen angepasst werden können und wie sie von fortgeschrittenen Interaktionskonzepten profitieren. Für die zweite Frage untersuche ich, wie insbesondere die räumliche Interaktion bei der Exploration von Daten in Mixed Reality helfen kann. Dabei betrachte ich die Interaktion mit räumlichen Geräten im Vergleich zur Touch-Eingabe, die Verwendung zusätzlicher mobiler Geräte als Controller und das Potenzial transparenter Interaktionspanels. Um die dritte Frage zu beantworten, stelle ich schließlich meine Forschung darüber vor, wie Benutzerinteraktion in immersiver Mixed-Reality direkt in der realen Umgebung analysiert werden kann und wie dies neue Erkenntnisse liefern kann. Insgesamt trage ich mit meiner Forschung durch Interaktions- und Visualisierungskonzepte, Software-Prototypen und Ergebnisse aus mehreren Nutzerstudien zu der Frage bei, wie räumliche Interaktionstechniken die Erkundung von immersiven Mixed-Reality-Visualisierungen unterstützen können

    Towards Intelligent Telerobotics: Visualization and Control of Remote Robot

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    Human-machine cooperative or co-robotics has been recognized as the next generation of robotics. In contrast to current systems that use limited-reasoning strategies or address problems in narrow contexts, new co-robot systems will be characterized by their flexibility, resourcefulness, varied modeling or reasoning approaches, and use of real-world data in real time, demonstrating a level of intelligence and adaptability seen in humans and animals. The research I focused is in the two sub-field of co-robotics: teleoperation and telepresence. We firstly explore the ways of teleoperation using mixed reality techniques. I proposed a new type of display: hybrid-reality display (HRD) system, which utilizes commodity projection device to project captured video frame onto 3D replica of the actual target surface. It provides a direct alignment between the frame of reference for the human subject and that of the displayed image. The advantage of this approach lies in the fact that no wearing device needed for the users, providing minimal intrusiveness and accommodating users eyes during focusing. The field-of-view is also significantly increased. From a user-centered design standpoint, the HRD is motivated by teleoperation accidents, incidents, and user research in military reconnaissance etc. Teleoperation in these environments is compromised by the Keyhole Effect, which results from the limited field of view of reference. The technique contribution of the proposed HRD system is the multi-system calibration which mainly involves motion sensor, projector, cameras and robotic arm. Due to the purpose of the system, the accuracy of calibration should also be restricted within millimeter level. The followed up research of HRD is focused on high accuracy 3D reconstruction of the replica via commodity devices for better alignment of video frame. Conventional 3D scanner lacks either depth resolution or be very expensive. We proposed a structured light scanning based 3D sensing system with accuracy within 1 millimeter while robust to global illumination and surface reflection. Extensive user study prove the performance of our proposed algorithm. In order to compensate the unsynchronization between the local station and remote station due to latency introduced during data sensing and communication, 1-step-ahead predictive control algorithm is presented. The latency between human control and robot movement can be formulated as a linear equation group with a smooth coefficient ranging from 0 to 1. This predictive control algorithm can be further formulated by optimizing a cost function. We then explore the aspect of telepresence. Many hardware designs have been developed to allow a camera to be placed optically directly behind the screen. The purpose of such setups is to enable two-way video teleconferencing that maintains eye-contact. However, the image from the see-through camera usually exhibits a number of imaging artifacts such as low signal to noise ratio, incorrect color balance, and lost of details. Thus we develop a novel image enhancement framework that utilizes an auxiliary color+depth camera that is mounted on the side of the screen. By fusing the information from both cameras, we are able to significantly improve the quality of the see-through image. Experimental results have demonstrated that our fusion method compares favorably against traditional image enhancement/warping methods that uses only a single image

    Spatial Displays and Spatial Instruments

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    The conference proceedings topics are divided into two main areas: (1) issues of spatial and picture perception raised by graphical electronic displays of spatial information; and (2) design questions raised by the practical experience of designers actually defining new spatial instruments for use in new aircraft and spacecraft. Each topic is considered from both a theoretical and an applied direction. Emphasis is placed on discussion of phenomena and determination of design principles

    Enhancing Perception and Immersion in Pre-Captured Environments through Learning-Based Eye Height Adaptation

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    Pre-captured immersive environments using omnidirectional cameras provide a wide range of virtual reality applications. Previous research has shown that manipulating the eye height in egocentric virtual environments can significantly affect distance perception and immersion. However, the influence of eye height in pre-captured real environments has received less attention due to the difficulty of altering the perspective after finishing the capture process. To explore this influence, we first propose a pilot study that captures real environments with multiple eye heights and asks participants to judge the egocentric distances and immersion. If a significant influence is confirmed, an effective image-based approach to adapt pre-captured real-world environments to the user's eye height would be desirable. Motivated by the study, we propose a learning-based approach for synthesizing novel views for omnidirectional images with altered eye heights. This approach employs a multitask architecture that learns depth and semantic segmentation in two formats, and generates high-quality depth and semantic segmentation to facilitate the inpainting stage. With the improved omnidirectional-aware layered depth image, our approach synthesizes natural and realistic visuals for eye height adaptation. Quantitative and qualitative evaluation shows favorable results against state-of-the-art methods, and an extensive user study verifies improved perception and immersion for pre-captured real-world environments.Comment: 10 pages, 13 figures, 3 tables, submitted to ISMAR 202

    Deep learning models for 3D mesh saliency prediction.

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    El estudio de la atención visual humana ha sido ampliamente explorado en muchos trabajos. Consiste en detectar e identificar las regiones del estímulo que más llaman la atención del usuario, generalmente utilizando un eye tracker para recolectar los datos. Esta medida de las regiones de interés se conoce como saliencia, y su detección y modelado es un problema fundamental en gráficos por computadora y visión por computadora. Esta tesis de fin de máster presenta un modelo de predicción de salienia para nubes de puntos basado en aprendizaje profundo.<br /

    Feature based estimation of myocardial motion from tagged MR images

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    In the past few years we witnessed an increase in mortality due to cancer relative to mortality due to cardiovascular diseases. In 2008, the Netherlands Statistics Agency reports that 33.900 people died of cancer against 33.100 deaths due to cardiovascular diseases, making cancer the number one cause of death in the Netherlands [33]. Even if the rate of people affected by heart diseases is continually rising, they "simply don’t die of it", according to the research director Prof. Mat Daemen of research institute CARIM of the University of Maastricht [50]. The reason for this is the early diagnosis, and the treatment of people with identified risk factors for diseases like ischemic heart disease, hypertrophic cardiomyopathy, thoracic aortic disease, pericardial (sac around the heart) disease, cardiac tumors, pulmonary artery disease, valvular disease, and congenital heart disease before and after surgical repair. Cardiac imaging plays a crucial role in the early diagnosis, since it allows the accurate investigation of a large amount of imaging data in a small amount of time. Moreover, cardiac imaging reduces costs of inpatient care, as has been shown in recent studies [77]. With this in mind, in this work we have provided several tools with the aim to help the investigation of the cardiac motion. In chapters 2 and 3 we have explored a novel variational optic flow methodology based on multi-scale feature points to extract cardiac motion from tagged MR images. Compared to constant brightness methods, this new approach exhibits several advantages. Although the intensity of critical points is also influenced by fading, critical points do retain their characteristic even in the presence of intensity changes, such as in MR imaging. In an experiment in section 5.4 we have applied this optic flow approach directly on tagged MR images. A visual inspection confirmed that the extracted motion fields realistically depicted the cardiac wall motion. The method exploits also the advantages from the multiscale framework. Because sparse velocity formulas 2.9, 3.7, 6.21, and 7.5 provide a number of equations equal to the number of unknowns, the method does not suffer from the aperture problem in retrieving velocities associated to the critical points. In chapters 2 and 3 we have moreover introduced a smoothness component of the optic flow equation described by means of covariant derivatives. This is a novelty in the optic flow literature. Many variational optic flow methods present a smoothness component that penalizes for changes from global assumptions such as isotropic or anisotropic smoothness. In the smoothness term proposed deviations from a predefined motion model are penalized. Moreover, the proposed optic flow equation has been decomposed in rotation-free and divergence-free components. This decomposition allows independent tuning of the two components during the vector field reconstruction. The experiments and the Table of errors provided in 3.8 showed that the combination of the smoothness term, influenced by a predefined motion model, and the Helmholtz decomposition in the optic flow equation reduces the average angular error substantially (20%-25%) with respect to a similar technique that employs only standard derivatives in the smoothness term. In section 5.3 we extracted the motion field of a phantom of which we know the ground truth of and compared the performance of this optic flow method with the performance of other optic flow methods well known in the literature, such as the Horn and Schunck [76] approach, the Lucas and Kanade [111] technique and the tuple image multi-scale optic flow constraint equation of Van Assen et al. [163]. Tests showed that the proposed optic flow methodology provides the smallest average angular error (AAE = 3.84 degrees) and L2 norm = 0.1. In this work we employed the Helmholtz decomposition also to study the cardiac behavior, since the vector field decomposition allows to investigate cardiac contraction and cardiac rotation independently. In chapter 4 we carried out an analysis of cardiac motion of ten volunteers and one patient where we estimated the kinetic energy for the different components. This decomposition is useful since it allows to visualize and quantify the contributions of each single vector field component to the heart beat. Local measurements of the kinetic energy have also been used to detect areas of the cardiac walls with little movement. Experiments on a patient and a comparison between a late enhancement cardiac image and an illustration of the cardiac kinetic energy on a bull’s eye plot illustrated that a correspondence between an infarcted area and an area with very small kinetic energy exists. With the aim to extend in the future the proposed optic flow equation to a 3D approach, in chapter 6 we investigated the 3D winding number approach as a tool to locate critical points in volume images. We simplified the mathematics involved with respect to a previous work [150] and we provided several examples and applications such as cardiac motion estimation from 3-dimensional tagged images, follicle and neuronal cell counting. Finally in chapter 7 we continued our investigation on volume tagged MR images, by retrieving the cardiac motion field using a 3-dimensional and simple version of the proposed optic flow equation based on standard derivatives. We showed that the retrieved motion fields display the contracting and rotating behavior of the cardiac muscle. We moreover extracted the through-plane component, which provides a realistic illustration of the vector field and is missed by 2-dimensional approaches
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