You are cordially invited to attend our CG Colloquium on Thursday, May 2nd, 2019, 15:45-17:45h, at Pulse Hall 4

The program features the following three speakers:

Huinan Jiang

Title: Player model analysis for adaptive content delivery in an educational game

Abstract: Player in games has been a useful way for understanding player motivation, style and preferences, assisting us to predict their behaviour, adapt the and improve user experience. For serious games, learning is also an factor to consider. Most work done in this area is about adaptive difficulty. While in our educational game Squla, students are exposed to multiple game types, it’s interesting to know how their behavioural data could their game type preference, and whether custom game type delivery could improve students’ engagement and learning. Therefore we present a player analysis method game adaptation, and experiment with target student groups to look into the impact.

Antony Löbker

Title: Automatic reconstruction of real-world buildings using open data

Abstract: Using publicly available data , such as Google streetview panoramas and OpenStreetMap building, it is possible to reconstruct real-world buildings. While these are not highly detailed, they will give a general impression of a. The proposed method can quickly reconstruction an entire neighbourhood in major urban centers around the world.

Julie Hongping Feng

Title: Building a 4D MRI blood flow statistical model

Abstract: Cardiovascular (CVDs) are the global number one cause of death. Current of CVDs is mainly based on functions and morphology of cardiovascular, and 4D MRI blood flow data has become a new and powerful source of, which allows both anatomical and functional analysis in a single. However, it is still difficult to efficiently utilize this data source diagnose CVDs. One of the main reasons is the lack of standard analysis and understanding of this rather new imaging modality. The method to understand the healthy behaviour and its variation is to build an atlas. Current blood flow atlas do not support 3D velocity vector field full information. We attempt to build a 4D MRI blood flow atlas similar to statistical shape and appearance models by applying Principal Component Analysis (PCA) to get the mean and main variations of the blood flow fields. The of this atlas would help physicians understand the 4D MRI data and assist them to identify whether the data is abnormal or not. In order to more efficient representations of variations for vector fields, we also tested Complex PCA and Quaternion PCA, besides traditional Real PCA. Finally, will visualize the results such that they can be interpretable.

You are cordially invited to attend our CG Colloquium on Thursday, April 18, 2019, 15:45-17:45h, at Pulse Hall 4 .

The program features the following three speakers:

Remi van der Laan

Title: Enhancing Compression of the Sparse Voxel Directed Acyclic Graph

Abstract: Rendering massive scenes in real time represented as voxels has emerged as an attractive alternative compared to the traditional rendering pipeline. This has been achieved through the development of data structures that can efficiently store the scene data while also being inexpensive to traverse. The Sparse Voxel Directed Acyclic Graph is such a data structure, which losslessly compresses geometry by exploiting the spatial coherence in the scene. We attempt enhance the effectiveness of this compression through modifications to the construction of the graph and investigate possibility of applying lossy compression techniques.

Hao Ming Ye

Title: not available at the moment

Abstract: not available at the moment

Ruben Wiersma

Title: Graph Convolutional Networks for Learning on Point Clouds

Abstract: In the past decade, Convolutional Neural Networks (CNNs) have achieved incredible results. A recent development in the deep learning community is the attempt to generalise the advantages of CNNs from a Euclidean domain to non-Euclidean domains, like graphs and manifolds. Some examples of graph data are social networks, regulatory networks, functional networks, and 3D shapes. We attempt to get an understanding of the methods currently available and aim to improve on the current methodology for learning on point clouds. A tentative conclusion is that the conceptually simple Graph Convolutional Network by Kipf and Welling could be improved for manifolds through the incorporation of the connection Laplacian from vector diffusion maps.

You are cordially invited to attend our Computer Graphics and Visualization Seminar on Thursday, April 4, 2019, 15:45-17:45h, at Pulse Hall 7.

The program features the following three speakers:

Ruben VroegindeWeij (PRELIMINARY)
Title: Motion in Image
Abstract: We present a method to encode motion in a single image by mixing frames from different time origins with a simple user interface.

Mark van de Ruit
Title: Pre-Estimated Spectral Rendering
Abstract: Spectral Monte-Carlo rendering algorithms are suited for reproducing several advanced light phenomena such as dispersion and colored particle scattering. However, spectral rendering comes at the cost of increased (colored) image noise, as now additional samples are required in the spectral domain. We propose to iteratively build estimates of the spectral distributions in a scene during rendering, and use these estimates to guide sampling of the spectral domain. This method can lower variance from spectral sampling in specific situations, which is demonstrated with a working implementation in a conventional path tracer.

Felix Yang
Title: Adaptive Multi-view Ambient Occlusion
Abstract: Screen-space ambient occlusion and obscurance is a group of techniques that approximate the ambient occlusion or obscurance lighting model in the screen-space. They are ubiquitously adopted in modern video games, but suffer from view-dependent artifacts. One possible method to remedy such artifacts is using additional auxiliary cameras to aid the computation, but the improvement diminishes if the auxiliary cameras have poor coverage of the main scene. This project aims to develop techniques to adaptively manipulate the auxiliary cameras to ensure good coverages, therefore a more stable improvement over the single-view result.

Computer Graphics and Visualization Seminar on Thursday, March 7, 2019, 15:45-17:45h, at EWI-Lecture hall Chip.

The program features the following two speakers:

Remi van der Laan

Title: Exploiting Coherence in Time-Varying Voxel Data

Abstract: We encode time-varying voxel data for efficient storage and streaming. We store the equivalent of a separate sparse voxel octree for each frame, but utilize both spatial and temporal coherence to reduce the amount of memory needed. We represent the time-varying voxel data in a single directed acyclic graph with one root per time step. In this graph, we avoid storing identical regions by keeping one unique instance and pointing to that from several parents. We further reduce the memory consumption of the graph by minimizing the number of bits per pointer and encoding the result into a dense bitstream.

Michiel van Spaendonck

Title: Spatiotemporal Variance-Guided Filtering: Real-Time Reconstruction for Path-Traced Global Illumination

Abstract: We introduce a reconstruction algorithm that generates a temporally stable sequence of images from one path-per-pixel global illumination. To handle such noisy input, we use temporal accumulation to increase the effective sample count and spatiotemporal luminance variance estimates to drive a hierarchical, image-space wavelet filter. This hierarchy allows us to distinguish between noise and detail at multiple scales using local luminance variance.

Physically based light transport is a long-standing goal for real-time computer graphics. While modern games use limited forms of ray tracing, physically based Monte Carlo global illumination does not meet their 30Hz minimal performance requirement. Looking ahead to fully dynamic real-time path tracing, we expect this to only be feasible using a small number of paths per pixel. As such, image reconstruction using low sample counts is key to bringing path tracing to real-time. When compared to prior interactive reconstruction filters, our work gives approximately 10x more temporally stable results, matches reference images 5-47% better (according to SSIM), and runs in just 10ms (+- 15%) on modern graphics hardware at 1920×1080 resolution.

You are cordially invited to attend our Computer Graphics and Visualization Seminar on Thursday, February 21, 2019, 15:45-17:45h, at EWI-Lecture hall Chip.

The program features the following two speakers:

Nouri Khalass
Title: Visualizing Stars and Emission Nebulae
Abstract: We describe the star and nebula visualization techniques used to create a 3D volumetric visualization of the Orion Nebula. The nebula’s ionization layer is modeled first as a surface model, derived from infrared and visible light observations. The model is imported into a volume scene graph-based volume visualization system to simulate the nebula’s emissive gases. Stars are rendered using Gaussian spots that are attenuated with distance.

Mark van de Ruit
Title: Real-Time Polygonal-Light Shading with Linearly Transformed Cosines
Abstract: In this paper, we show that applying a linear transformation—represented by a 3 x 3 matrix—to the direction vectors of a spherical distribution yields another spherical distribution, for which we derive a closed-form expression. With this idea, we can use any spherical distribution as a base shape to create a new family of spherical distributions with parametric roughness, elliptic anisotropy and skewness. If the original distribution has an analytic expression, normalization, integration over spherical polygons, and importance sampling, then these properties are inherited by the linearly transformed distributions.

By choosing a clamped cosine for the original distribution we obtain a family of distributions, which we call Linearly Transformed Cosines (LTCs), that provide a good approximation to physically based BRDFs and that can be analytically integrated over arbitrary spherical polygons. We show how to use these properties in a realtime polygonal-light shading application. Our technique is robust, fast, accurate and simple to implement.