Category Archives: Archive

CG Colloquium Thursday November 15th

You are cordially invited to attend our Computer Graphics and Visualization Seminar on Thursday, November 15th, 2018, 15:45-17:45h, at Pulse-Hall 2.

The program features the following two speakers:

Huinan Jiang
A Chebyshev Semi-Iterative Approach for Accelerating Projective and Position-based Dynamics
In this paper, we study the use of the Chebyshev semi-iterative approach in projective and position-based dynamics. Although projective dynamics is fundamentally nonlinear, its convergence behavior is similar to that of an iterative method solving a linear system. Because of that, we can estimate the “spectral radius” and use it in the Chebyshev approach to accelerate the convergence by at least one order of magnitude, when the global step is handled by the direct solver, the Jacobi solver, or even the Gauss-Seidel solver. Our experiment shows that the combination of the Chebyshev approach and the direct solver runs fastest on CPU, while the combination of the Chebyshev approach and the Jacobi solver outperforms any other combination on GPU, as it is highly compatible with parallel computing. Our experiment further shows position-based dynamics can be accelerated by the Chebyshev approach as well, although the effect is less obvious for tetrahedral meshes. The whole approach is simple, fast, effective, GPU-friendly, and has a small memory cost.

Jesse Tilro
Phase-Functioned Neural Networks for Character Control
We present a real-time character control mechanism using a novel neural network architecture called a Phase-Functioned Neural Network. In this network structure, the weights are computed via a cyclic function which uses the phase as an input. Along with the phase, our system takes as input user controls, the previous state of the character, the geometry of the scene, and automatically produces high quality motions that achieve the desired user control. The entire network is trained in an end-to-end fashion on a large dataset composed of locomotion such as walking, running, jumping, and climbing movements fitted into virtual environments. Our system can therefore automatically produce motions where the character adapts to different geometric environments such as walking and running over rough terrain, climbing over large rocks, jumping over obstacles, and crouching under low ceilings. Our network architecture produces higher quality results than time-series autoregressive models such as LSTMs as it deals explicitly with the latent variable of motion relating to the phase. Once trained, our system is also extremely fast and compact, requiring only milliseconds of execution time and a few megabytes of memory, even when trained on gigabytes of motion data. Our work is most appropriate for controlling characters in interactive scenes such as computer games and virtual reality systems.

CG Colloquium Thursday November 1st

You are cordially invited to attend our Computer Graphics and Visualization Seminar on Thursday, November 1st, 2018, 15:45-17:45h, at Pulse-Hall 4.

The program features the following two speakers:

Youri Appel
Towards Virtual Reality Infinite Walking: Dynamic Saccadic Redirection
Redirected walking techniques can enhance the immersion and visual-vestibular comfort of virtual reality (VR) navigation, but are often limited by the size, shape, and content of the physical environments.
We propose a redirected walking technique that can apply to small physical environments with static or dynamic obstacles. Via a head- and eye-tracking VR headset, our method detects saccadic suppression and redirects the users during the resulting temporary blindness. Our dynamic path planning runs in real-time on a GPU, and thus can avoid static and dynamic obstacles, including walls, furniture, and other VR users sharing the same physical space. To further enhance saccadic redirection, we propose subtle gaze direction methods tailored for VR perception.
We demonstrate that saccades can significantly increase the rotation gains during redirection without introducing visual distortions or simulator sickness. This allows our method to apply to large open virtual spaces and small physical environments for room-scale VR. We evaluate our system via numerical simulations and real user studies.

Berend Baas
Guided proceduralization: Optimizing geometry processing and grammar extraction for architectural models
We describe a guided proceduralization framework that optimizes geometry processing on architectural input models to extract target grammars. We aim to provide efficient artistic workflows by creating procedural representations from existing 3D models, where the procedural expressiveness is controlled by the user. Architectural reconstruction and modeling tasks have been handled as either time consuming manual processes or procedural generation with difficult control and artistic influence. We bridge the gap between creation and generation by converting existing manually modeled architecture to procedurally editable parametrized models, and carrying the guidance to procedural domain by letting the user define the target procedural representation. Additionally, we propose various applications of such procedural representations, including guided completion of point cloud models, controllable 3D city modeling, and other benefits of procedural modeling.

CG Colloquium Thursday October 4th

You are cordially invited to attend our Computer Graphics and Visualization Seminar on Thursday, October 4, 2018, 15:45-17:45h, at Pulse-Hall 4.

The program features the following two speakers:

Mathijs Molenaar

Title: Occlusion culling in memory-coherent ray tracing


In this project I look to improve the performance of out-of-core ray/path tracing based on memory-coherent ray tracing. In memory-coherent ray tracing the acceleration structure is split into two layers, the first of which is always in memory while the subtrees in the second layer are evicted from memory when deemed necessary. Rays are batched at unloaded leaf nodes (in the top-level tree) and only when a batch is full will the leaf node be loaded from disk and intersected. My research question is whether rendering performance can be improved by keeping a low-resolution representation of each top-level leaf node in memory at all time and using it as an early-out for rays hitting a leaf’s bounding volume. This will reduce the number of disk operations at the cost of some extra computation time.

Wouter Groen

Title: Precomputed Light-Transport Networks for Volume Rendering


Rendering volumetric data including complex lighting phenomena is a difficult task.

Previous solutions, such as in Exposure Render, involve a Monte Carlo Processes that has to shoot many rays in order to approximate the light transport faithfully. In consequence, the process is costly and efficient image synthesis becomes challenging. In this project, we want to investigate the principal of path reusing by building a network of light-transport paths in a preprocess. Hereby, we avoid the costly process of establishing new branching for each ray that is traversing the volume. This talk will be an initialization talk, in which we describe the goals that we will pursue in the months to come.

Our initial plan is as follows. Given a volumetric data set, we want to precompute the result of a set of rays within this volume, which will be steered by the volume data itself by mechanisms, such as importance sampling. These rays will be connected to establish a light-transport network. Our goal is to make use of this light-transport network to accelerate the computation of an approximate light transport at run-time. When rendering, we will launch rays from the light/camera and will connect these rays to the precomputed network. Next, the involved energies coming from the rays, will simply be propagated along the paths of the network to estimate an overall light contribution. In this way, only few new intersection tests need to be performed, while many paths in the network are reused. Hereby, run-time costs are reduced drastically with, hopefully, little visual impact. There are several research questions to be answered: How to represent and store the network efficiently? How to derive it in a fast way? How to structure the computations efficiently? How to enable an unbiased result?…

MSc thesis defense Monday 17th September

You are cordially invited to attend the MSc thesis defense of Anshul Khandelwal, titled Reservoir Characterization using a Geometric Approach.

The defense will take place on Monday, 17th September at 14:00h in room Colloquimzaal 0.E420 at Van Mourik Broekmanweg.

The presentation is open to the public and will last around 40 minutes including questions from the audience. You are hereby cordially invited to join!

Reservoir Characterization using a Geometric Approach

Quantifying the anthropogenic impacts such as reservoir characterization is a big challenge in the field of water management. In this work, a computer graphics based geometric approach is presented which can predict the underlying topology of large-scale reservoirs. The proposed algorithm uses freely available, satellite based landscape data of the surrounding regions to predict reservoir characteristics. The premise of the presented approach is that the slope of the surrounding landscape is an important determinant to understand the underlying landscape of the reservoirs. This method outperforms the existing state-of-the-art techniques used to estimate the storage capacities drastically, both in terms of estimated maximum volume stored and estimated volume area curves. Evaluation of the geometric model presented is done on 28 reservoirs using the HydroSHEDs data which was developed using the Shuttle RADAR Topography Mission conducted by NASA. This HydroSHEDs data was obtained in 2000 which acts as ground truth data for the reservoirs built after 2000. Further, model parameters are introduced to improve the modeling capabilities of the reconstructed reservoirs. This approach further intensifies the case of using computer graphics techniques for raster based analysis and provides a platform for further research in the field of water management.

Prof. Dr. Elmar Eisemann
Dr. Klaus Hildebrandt
Dr. Cynthia C.S. Liem
Prof. Dr. Nick van de Giesen

Delft Data Science Seminar – Visual Data Science and its role in Computational Medicine

Tuesday the 6th of Februari the Delft Data Science Seminar takes place at the Faculty of Aerospace and Engineering at TU Delft.

The Computer Graphics and Visualization Group of TU Delft Data Science, in cooperation with prof. Helwig Hauser from the University of Bergen (Norway), organise this one-day workshop where evolutionary new opportunities in data science and technology are combined in visualisation and medicine in methods such as neuroimaging and machine learning.

We are glad that eight high-profile speakers have accepted our invitation to talk at this workshop. They will comment on a variety of topics, including visual data science vs. classical science, on computational vs. interactive approaches and on the role of the human in visual data science.

Join us on Tuesday the 6th of February from 10 AM till 5 PM for the Delft Data Science Seminar – Visual Data Science and its role in Computational Medicine.

Workshop program (links to slides): 

09h30 welcome & registration

10h00 opening (DDS / TU Delft, Univ. of Bergen)

10h10 session 1: computational & visual solutions in biomedicine (chair: H. Hauser)

11h10 coffee break

11h30 session 2: neuroimaging and visual data science (chair: A. Vilanova)

12h30 lunch

13h30 session 3: data science with statistics & machine learning (chair: E. Eisemann)

14h30 coffee break

14h50 session 4: visual data science with visualization & visual analytics (chair: H. Hauser)

16h00 panel discussion

The panel focused on having different views on relevant aspects of visual data science. Visual data science vs. classical science (indicating the change of paradigm on how to identify hypothesis), on computational vs. interactive visual approaches (challenges and opportunities), on the role of the human in visual data science.


16h45 closing (DDS / TU Delft, Univ. of Bergen)

17h00 drinks


Recent PhD defenses

Two new doctors graduated from our group at the end of 2014 in the field of medical visualization:

  • Dr. Peter Kok successfully defended his PhD. In his thesis, ‘Integrative Visualization of Whole Body Molecular Imaging Data‘, Dr. Kok present methods to map molecular imaging data to a common reference frame, to combine multiple modalities and to compare scans taken at different timepoints. The full text of the thesis is available here.
Dr. Kok with his paranymphs and the thesis committee members.
Dr. Kok with his paranymphs and the thesis committee members. tblr: Jos Roerdink, Elmar Eisemann, Charl Botha, Erik Jansen, Boudewijn Lelieveldt, beadle Rina Abbriata, Louise van der Weerd, Bernhard Preim, Noeska Smit, Peter Kok, Thomas Kroes and the head of the committee.
  • On the same day, Dr. Stef Busking also successfully defended his PhD. His thesis, ‘Visualization of Variation and Variability‘ deals with comparative visualization as a means to analyze variation or variability based on two or more specific instances of the data. The full text of the thesis is available here.

We would like to congratulate to both doctors with their accomplishments.

Elmar Eisemann’s inauguration speech: today at 15:00 in the TU Delft Aula!

Today, Elmar Eisemann, the head of our Computer Graphics and Visualization group, will be delivering his inauguration speech at 3 pm in the TU Delft Aula. Don’t miss this once in a lifetime opportunity to hear about, and see, the many exciting possibilities and application areas of computer graphics. Find out in what directions our group will develop in and join us this afternoon at the aula auditorium. Check out the full invitation here!

MSc thesis successfully defended last week

Casper van Leeuwen successfully defended his thesis ‘Spatial-temporal pathline clustering based on FTLE fields‘ in our group on the 14th of May.

Casper van Leeuwen defending his thesis
Casper van Leeuwen defending his thesis

In his work, Casper worked with cardiac flow acquisition data consisting of 3D blood flow of the heart featuring 4D vector fields. These 4D vector fields of the heart are used in clinical research to gain insight in the flow patterns within the heart which in turn can be used to gain a better understanding of the pathogenesis of cardiovascular diseases. He implemented a visualization technique called Spatial-temporal Clustering based on Finite Time Lyapunov Exponents, that aims to circumvent the challenges posed by the structural complexity of the flow and give a concise and insightful representation of the blood flow patterns within the heart. Aside from the main visualization technique this works also introduces a novel probing technique that highlights the base principles of the FTLE fields to provide the user with a better understanding of how a FTLE field works.

Casper van Leeuwen receives his MSc degree
Casper van Leeuwen receives his MSc degree

We would like to congratulate Casper with his achievement and new title and wish him all the best for the future!

Presentation and Paper Award at i3D 2014


At i3D 2014, our paper “Prefiltered Single Scattering” (Oliver Klehm et al.) received two awards.
It was chosen for the JCGT selection and it won the third place presentation award!

The approach allows rendering of participating media at very low cost with high quality, which makes it interesting for many interactive applications!

Congratulations everyone!