Virtual reality application applied to biomedical models reconstructed from CT scanning

Postprint (published version

Ecodevelopment, Gender, and Empowerment: Perspectives from India’s Protected Area Communities

Book abstract: Feminism has re-shaped the way we think about equality, power relations and social change. Recent feminist scholarship has provided new theoretical frameworks, methodologies and empirical analyses of how gender and feminism are situated within the development process.Global Perspectives on Gender and Space: Engaging Feminism and Development draws upon this framework to explore the effects of globalization on development in diverse geographical contexts. It explores how women’s and men’s lives are gendered in specific spaces as well as across multiple landscapes

Optical flow estimation via steered-L1 norm

Global variational methods for estimating optical flow are among the best performing methods due to the subpixel accuracy and the ‘fill-in’ effect they provide. The fill-in effect allows optical flow displacements to be estimated even in low and untextured areas of the image. The estimation of such displacements are induced by the smoothness term. The L1 norm provides a robust regularisation term for the optical flow energy function with a very good performance for edge-preserving. However this norm suffers from several issues, among these is the isotropic nature of this norm which reduces the fill-in effect and eventually the accuracy of estimation in areas near motion boundaries. In this paper we propose an enhancement to the L1 norm that improves the fill-in effect for this smoothness term. In order to do this we analyse the structure tensor matrix and use its eigenvectors to steer the smoothness term into components that are ‘orthogonal to’ and ‘aligned with’ image structures. This is done in primal-dual formulation. Results show a reduced end-point error and improved accuracy compared to the conventional L1 norm

Distributed OpenGL Rendering in Network Bandwidth Constrained Environments

Display walls made from multiple monitors are often used when very high resolution images are required. To utilise a display wall, rendering information must be sent to each computer that the monitors are connect to. The network is often the performance bottleneck for demanding applications, like high performance 3D animations. This paper introduces ClusterGL; a distribution library for OpenGL applications. ClusterGL reduces network traffic by using compression, frame differencing and multi-cast. Existing applications can use ClusterGL without recompilation. Benchmarks show that, for most applications, ClusterGL outperforms other systems that support unmodified OpenGL applications including Chromium and BroadcastGL. The difference is larger for more complex scene geometries and when there are more display machines. For example, when rendering OpenArena, ClusterGL outperforms Chromium by over 300% on the Symphony display wall at The University of Waikato, New Zealand. This display has 20 monitors supported by five computers connected by gigabit Ethernet, with a full resolution of over 35 megapixels. ClusterGL is freely available via Google Code

Improving Information Perception of Graphical Displays – an Experimental Study on the Display of Column Graphs

Due to the fact that the quality of decisions is linked to the availability of information and to the ability of the human brain to process this in an effective and efficient way, its selection and representation are of major importance in business communication. Graphs and tables are widely used to transform raw data into a more understandable format, but there are not any empirically tested guidelines that consider the cognition and perception abilities of humans. This paper therefore explores how specific visual designs applied to column graphs influence effectiveness and efficiency by applying the technique of eye-tracking to make an accurate assessment of what the observer is looking at. The tested design elements show significant results and allow the deduction of the following design guidelines for column graphs: do not use a 3D view for depicting two dimensional data, do not use non-zero or broken axes, do show label values, do not use horizontal gridlines or the label axis when showing label values and do align the label values depending on the available space (either horizontally or vertically)

Optical flow estimation via steered-L1 norm

Global variational methods for estimating optical flow are among the best performing methods due to the subpixel accuracy and the ‘fill-in’ effect they provide. The fill-in effect allows optical flow displacements to be estimated even in low and untextured areas of the image. The estimation of such displacements are induced by the smoothness term. The L1 norm provides a robust regularisation term for the optical flow energy function with a very good performance for edge-preserving. However this norm suffers from several issues, among these is the isotropic nature of this norm which reduces the fill-in effect and eventually the accuracy of estimation in areas near motion boundaries. In this paper we propose an enhancement to the L1 norm that improves the fill-in effect for this smoothness term. In order to do this we analyse the structure tensor matrix and use its eigenvectors to steer the smoothness term into components that are ‘orthogonal to’ and ‘aligned with’ image structures. This is done in primal-dual formulation. Results show a reduced end-point error and improved accuracy compared to the conventional L1 norm

Glyphs for space-time Jacobians of time-dependent vector fields

Glyphs have proven to be a powerful visualization technique for general tensor fields modeling physical phenomena such as diffusion or the derivative of flow fields. Most glyph constructions, however, do not provide a way of considering the temporal derivative, which is generally nonzero in non-stationary vector fields. This derivative offers a deeper understanding of features in time-dependent vector fields. We introduce an extension to 2D and 3D tensor glyph design that additionally encodes the temporal information of velocities, and thus makes it possible to represent time-dependent Jacobians. At the same time, a certain set of requirements for general tensor glyphs is fulfilled, such that the new method provides a visualization of the steadiness or unsteadiness of a vector field at a given instance of time