Scalable wavelet-based coding of irregular meshes with interactive region-of-interest support

This paper proposes a novel functionality in wavelet-based irregular mesh coding, which is interactive region-of-interest (ROI) support. The proposed approach enables the user to define the arbitrary ROIs at the decoder side and to prioritize and decode these regions at arbitrarily high-granularity levels. In this context, a novel adaptive wavelet transform for irregular meshes is proposed, which enables: 1) varying the resolution across the surface at arbitrarily fine-granularity levels and 2) dynamic tiling, which adapts the tile sizes to the local sampling densities at each resolution level. The proposed tiling approach enables a rate-distortion-optimal distribution of rate across spatial regions. When limiting the highest resolution ROI to the visible regions, the fine granularity of the proposed adaptive wavelet transform reduces the required amount of graphics memory by up to 50%. Furthermore, the required graphics memory for an arbitrary small ROI becomes negligible compared to rendering without ROI support, independent of any tiling decisions. Random access is provided by a novel dynamic tiling approach, which proves to be particularly beneficial for large models of over 10(6) similar to 10(7) vertices. The experiments show that the dynamic tiling introduces a limited lossless rate penalty compared to an equivalent codec without ROI support. Additionally, rate savings up to 85% are observed while decoding ROIs of tens of thousands of vertices

Selective BRDFs for High Fidelity Rendering

High fidelity rendering systems rely on accurate material representations to produce a realistic visual appearance. However, these accurate models can be slow to evaluate. This work presents an approach for approximating these high accuracy reflectance models with faster, less complicated functions in regions of an image which possess low visual importance. A subjective rating experiment was conducted in which thirty participants were asked to assess the similarity of scenes rendered with low quality reflectance models, a high quality data-driven model and saliency based hybrids of those images. In two out of the three scenes that were evaluated significant differences were not found between the hybrid and reference images. This implies that in less visually salient regions of an image computational gains can be achieved by approximating computationally expensive materials with simpler analytic models

Multi-Modal Perception for Selective Rendering

A major challenge in generating high-fidelity virtual environments (VEs) is to be able to provide realism at interactive rates. The high-fidelity simulation of light and sound is still unachievable in real-time as such physical accuracy is very computationally demanding. Only recently has visual perception been used in high-fidelity rendering to improve performance by a series of novel exploitations; to render parts of the scene that are not currently being attended to by the viewer at a much lower quality without the difference being perceived. This paper investigates the effect spatialised directional sound has on the visual attention of a user towards rendered images. These perceptual artefacts are utilised in selective rendering pipelines via the use of multi-modal maps. The multi-modal maps are tested through psychophysical experiments to examine their applicability to selective rendering algorithms, with a series of fixed cost rendering functions, and are found to perform significantly better than only using image saliency maps that are naively applied to multi-modal virtual environments

Inviwo -- A Visualization System with Usage Abstraction Levels

The complexity of today's visualization applications demands specific visualization systems tailored for the development of these applications. Frequently, such systems utilize levels of abstraction to improve the application development process, for instance by providing a data flow network editor. Unfortunately, these abstractions result in several issues, which need to be circumvented through an abstraction-centered system design. Often, a high level of abstraction hides low level details, which makes it difficult to directly access the underlying computing platform, which would be important to achieve an optimal performance. Therefore, we propose a layer structure developed for modern and sustainable visualization systems allowing developers to interact with all contained abstraction levels. We refer to this interaction capabilities as usage abstraction levels, since we target application developers with various levels of experience. We formulate the requirements for such a system, derive the desired architecture, and present how the concepts have been exemplary realized within the Inviwo visualization system. Furthermore, we address several specific challenges that arise during the realization of such a layered architecture, such as communication between different computing platforms, performance centered encapsulation, as well as layer-independent development by supporting cross layer documentation and debugging capabilities

Virtual Reality Games for Motor Rehabilitation

This paper presents a fuzzy logic based method to track user satisfaction without the need for devices to monitor users physiological conditions. User satisfaction is the key to any product’s acceptance; computer applications and video games provide a unique opportunity to provide a tailored environment for each user to better suit their needs. We have implemented a non-adaptive fuzzy logic model of emotion, based on the emotional component of the Fuzzy Logic Adaptive Model of Emotion (FLAME) proposed by El-Nasr, to estimate player emotion in UnrealTournament 2004. In this paper we describe the implementation of this system and present the results of one of several play tests. Our research contradicts the current literature that suggests physiological measurements are needed. We show that it is possible to use a software only method to estimate user emotion