630 research outputs found
Developing serious games for cultural heritage: a state-of-the-art review
Although the widespread use of gaming for leisure purposes has been well documented, the use of games to support cultural heritage purposes, such as historical teaching and learning, or for enhancing museum visits, has been less well considered. The state-of-the-art in serious game technology is identical to that of the state-of-the-art in entertainment games technology. As a result, the field of serious heritage games concerns itself with recent advances in computer games, real-time computer graphics, virtual and augmented reality and artificial intelligence. On the other hand, the main strengths of serious gaming applications may be generalised as being in the areas of communication, visual expression of information, collaboration mechanisms, interactivity and entertainment. In this report, we will focus on the state-of-the-art with respect to the theories, methods and technologies used in serious heritage games. We provide an overview of existing literature of relevance to the domain, discuss the strengths and weaknesses of the described methods and point out unsolved problems and challenges. In addition, several case studies illustrating the application of methods and technologies used in cultural heritage are presented
Serious Games in Cultural Heritage
Although the widespread use of gaming for leisure purposes has been well documented, the use of games to support cultural heritage purposes, such as historical teaching and learning, or for enhancing museum visits, has been less well considered. The state-of-the-art in serious game technology is identical to that of the state-of-the-art in entertainment games technology. As a result the field of serious heritage games concerns itself with recent advances in computer games, real-time computer graphics, virtual and augmented reality and artificial intelligence. On the other hand, the main strengths of serious gaming applications may be generalised as being in the areas of communication, visual expression of information, collaboration mechanisms, interactivity and entertainment. In this report, we will focus on the state-of-the-art with respect to the theories, methods and technologies used in serious heritage games. We provide an overview of existing literature of relevance to the domain, discuss the strengths and weaknesses of the described methods and point out unsolved problems and challenges. In addition, several case studies illustrating the application of methods and technologies used in cultural heritage are presented
Efficient From-Point Visibility for Global Illumination in Virtual Scenes with Participating Media
Sichtbarkeitsbestimmung ist einer der fundamentalen Bausteine fotorealistischer Bildsynthese. Da die Berechnung der Sichtbarkeit allerdings äußerst kostspielig zu berechnen ist, wird nahezu die gesamte Berechnungszeit darauf verwendet. In dieser Arbeit stellen wir neue Methoden zur Speicherung, Berechnung und Approximation von Sichtbarkeit in Szenen mit streuenden Medien vor, die die Berechnung erheblich beschleunigen, dabei trotzdem qualitativ hochwertige und artefaktfreie Ergebnisse liefern
Mobile graphics: SIGGRAPH Asia 2017 course
Peer ReviewedPostprint (published version
Feature-driven Volume Visualization of Medical Imaging Data
Direct volume rendering (DVR) is a volume visualization technique that has been proved to be a very powerful tool in many scientific visualization domains. Diagnostic medical imaging is one such domain in which DVR provides new capabilities for the analysis of complex cases and improves the efficiency of image interpretation workflows. However, the full potential of DVR in the medical domain has not yet been realized. A major obstacle for a better integration of DVR in the medical domain is the time-consuming process to optimize the rendering parameters that are needed to generate diagnostically relevant visualizations in which the important features that are hidden in image volumes are clearly displayed, such as shape and spatial localization of tumors, its relationship with adjacent structures, and temporal changes in the tumors. In current workflows, clinicians must manually specify the transfer function (TF), view-point (camera), clipping planes, and other visual parameters. Another obstacle for the adoption of DVR to the medical domain is the ever increasing volume of imaging data. The advancement of imaging acquisition techniques has led to a rapid expansion in the size of the data, in the forms of higher resolutions, temporal imaging acquisition to track treatment responses over time, and an increase in the number of imaging modalities that are used for a single procedure. The manual specification of the rendering parameters under these circumstances is very challenging. This thesis proposes a set of innovative methods that visualize important features in multi-dimensional and multi-modality medical images by automatically or semi-automatically optimizing the rendering parameters. Our methods enable visualizations necessary for the diagnostic procedure in which 2D slice of interest (SOI) can be augmented with 3D anatomical contextual information to provide accurate spatial localization of 2D features in the SOI; the rendering parameters are automatically computed to guarantee the visibility of 3D features; and changes in 3D features can be tracked in temporal data under the constraint of consistent contextual information. We also present a method for the efficient computation of visibility histograms (VHs) using adaptive binning, which allows our optimal DVR to be automated and visualized in real-time. We evaluated our methods by producing visualizations for a variety of clinically relevant scenarios and imaging data sets. We also examined the computational performance of our methods for these scenarios
Interactive real-time three-dimensional visualisation of virtual textiles
Virtual textile databases provide a cost-efficient alternative to the use of existing hardcover
sample catalogues. By taking advantage of the high performance features offered by the
latest generation of programmable graphics accelerator boards, it is possible to combine
photometric stereo methods with 3D visualisation methods to implement a virtual textile
database. In this thesis, we investigate and combine rotation invariant texture retrieval with
interactive visualisation techniques.
We use a 3D surface representation that is a generic data representation that allows us to
combine real-time interactive 3D visualisation methods with present day texture retrieval
methods. We begin by investigating the most suitable data format for the 3D surface
representation and identify relief-mapping combined with Bézier surfaces as the most
suitable 3D surface representations for our needs, and go on to describe how these
representation can be combined for real-time rendering. We then investigate ten different
methods of implementing rotation invariant texture retrieval using feature vectors. These
results show that first order statistics in the form of histogram data are very effective for
discriminating colour albedo information, while rotation invariant gradient maps are
effective for distinguishing between different types of micro-geometry using either first or
second order statistics.Engineering and physical Sciences Research (EPSRC
Feature-driven Volume Visualization of Medical Imaging Data
Direct volume rendering (DVR) is a volume visualization technique that has been proved to be a very powerful tool in many scientific visualization domains. Diagnostic medical imaging is one such domain in which DVR provides new capabilities for the analysis of complex cases and improves the efficiency of image interpretation workflows. However, the full potential of DVR in the medical domain has not yet been realized. A major obstacle for a better integration of DVR in the medical domain is the time-consuming process to optimize the rendering parameters that are needed to generate diagnostically relevant visualizations in which the important features that are hidden in image volumes are clearly displayed, such as shape and spatial localization of tumors, its relationship with adjacent structures, and temporal changes in the tumors. In current workflows, clinicians must manually specify the transfer function (TF), view-point (camera), clipping planes, and other visual parameters. Another obstacle for the adoption of DVR to the medical domain is the ever increasing volume of imaging data. The advancement of imaging acquisition techniques has led to a rapid expansion in the size of the data, in the forms of higher resolutions, temporal imaging acquisition to track treatment responses over time, and an increase in the number of imaging modalities that are used for a single procedure. The manual specification of the rendering parameters under these circumstances is very challenging. This thesis proposes a set of innovative methods that visualize important features in multi-dimensional and multi-modality medical images by automatically or semi-automatically optimizing the rendering parameters. Our methods enable visualizations necessary for the diagnostic procedure in which 2D slice of interest (SOI) can be augmented with 3D anatomical contextual information to provide accurate spatial localization of 2D features in the SOI; the rendering parameters are automatically computed to guarantee the visibility of 3D features; and changes in 3D features can be tracked in temporal data under the constraint of consistent contextual information. We also present a method for the efficient computation of visibility histograms (VHs) using adaptive binning, which allows our optimal DVR to be automated and visualized in real-time. We evaluated our methods by producing visualizations for a variety of clinically relevant scenarios and imaging data sets. We also examined the computational performance of our methods for these scenarios
Gen-NeRF: Efficient and Generalizable Neural Radiance Fields via Algorithm-Hardware Co-Design
Novel view synthesis is an essential functionality for enabling immersive
experiences in various Augmented- and Virtual-Reality (AR/VR) applications, for
which generalizable Neural Radiance Fields (NeRFs) have gained increasing
popularity thanks to their cross-scene generalization capability. Despite their
promise, the real-device deployment of generalizable NeRFs is bottlenecked by
their prohibitive complexity due to the required massive memory accesses to
acquire scene features, causing their ray marching process to be
memory-bounded. To this end, we propose Gen-NeRF, an algorithm-hardware
co-design framework dedicated to generalizable NeRF acceleration, which for the
first time enables real-time generalizable NeRFs. On the algorithm side,
Gen-NeRF integrates a coarse-then-focus sampling strategy, leveraging the fact
that different regions of a 3D scene contribute differently to the rendered
pixel, to enable sparse yet effective sampling. On the hardware side, Gen-NeRF
highlights an accelerator micro-architecture to maximize the data reuse
opportunities among different rays by making use of their epipolar geometric
relationship. Furthermore, our Gen-NeRF accelerator features a customized
dataflow to enhance data locality during point-to-hardware mapping and an
optimized scene feature storage strategy to minimize memory bank conflicts.
Extensive experiments validate the effectiveness of our proposed Gen-NeRF
framework in enabling real-time and generalizable novel view synthesis.Comment: Accepted by ISCA 202
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