Category Archives: Colloquia

CG Colloquium Thursday September 20th

You are cordially invited to attend our next Computer Graphics Colloquium, which will be held on:

Thursday, September 20th, 2018, 15:45-16:45h, at EWI-Lecture Room F.

The programme features a guest talk.

Speaker: Liangliang Nan, Assistant Professor, 3D Geoinformation Group, Faculty of Architecture and the Built Environment, Delft University of Technology

Title: Modeling Real-World Scenes
Abstract: Capturing the real world scenes in the 3D format has been made possible by advances in scanning and photogrammetric technologies. This has attracted increasing interests in acquiring, analyzing, and modeling real-world scenes. However, obtaining a faithful 3D representation of real-world scenes still remains an open problem. In this talk, I would like to share my experiences in the past few years in reconstructing urban scenes. In particular, I will present two algorithms for reconstructing coarse models and for enriching the coarse models with fine details respectively. In the end, we will discuss the trend and some topics for the future research.

First CG Colloquium (2018/2019) – Thursday September 6th

The objective of the colloquium/seminar is a bi-weekly meeting to provide all CGV members, staff as well as graduate students, with a forum for
communication, presentation and scientific discussion in the area of Computer Graphics and Visualization at large. Please see this file for a more detailed description.

The first CG Colloquium for academic year 2018/2019 will be held on Thursday, 6th-September. The first session will be an introduction to the seminar/colloquium for master students. Only staff and the seminar students are expected to attend.


CGV Colloquium – Friday June 8th

You are cordially invited to attend our next Computer Graphics and Visualization (CGV) Seminar/ Colloquium, which will be held on:

Friday, June 8th, 2018, 15:45-16:45h, at EWI-Lecture Hall Pi.

The programme features a MSc graduation project midterm presentations.

Presenter 1: Anshul Khandelwal

Title: Reservoir Characterization using a Geometric Approach

Abstract: The project is aimed at calculating the storage capacities of water reservoirs built after 2000 using remote sensing data of the surrounding landscapes. The motivation of the project is to improve the anthropogenic impacts on Global Hydrological Models (GHMs) used to predict water availability globally. Evaluation of the model will be done using the Shuttle RADAR Topography Mission (SRTM) data collected by NASA in 2000.

CGV Colloquium – Friday May 25th

You are cordially invited to attend our next Computer Graphics and Visualization (CGV) Seminar/ Colloquium, which will be held on:

Friday, May 25th, 2018, 15:45-17:45h, at EWI-Lecture Hall Pi.

The programme features one MSc graduation project midterm presentations and a presentation of a research project by one of our PhD students.

Presenter 1: Yunchao Yin

Title: Annotation of cerebral angiography,

Abstract: Cerebral angiography is a medical imaging technique that used to visualize the vessels around the brain and provide quantitative measures for pathological changes such as arteriovenous malformations and aneurysms. However, it’s difficult for patients and young clinical stuff to tell the name of each vessel in the angiography. This project plans to create an automatic cerebral vessel name annotation tool based on deep learning. Semantic segmentation and topological skeleton extraction are both possible to realize automatic vessel names annotation, but the ground truth for semantic segmentation is relatively hard to get and pixel-wise perfect is not required for this task, so skeleton extraction is chosen. The project could be divided into two part: 1) angiography acquirement angle classification; 2) Vessel bifurcation detection. Different cerebral vascular model is used for angiography annotation of different projection angles, and the second part of the project predicts vessel names.

Presenter 2: Chaoran Fan

Title: Fast and accurate CNN-based brushing in scatterplots

Abstract: Brushing plays a central role in most modern visual analytics solutions and effective and efficient techniques for data selection are key to establishing a successful human-computer dialogue. With this paper, we address the need for brushing techniques that are both fast, enabling a fluid interaction in visual data exploration and analysis, and also accurate, i.e., enabling the user to effectively select specific data subsets, even when their geometric delimination is non-trivial. We present a new solution for a near-perfect sketch-based brushing technique, where we exploit a convolutional neural network (CNN) for estimating the intended data selection from a fast and simple click-and-drag interaction and from the data distribution in the visualization. Our key contributions include a drastically reduced error rate—now below 3%, i.e., less than half of the so far best accuracy— and an extension to a larger variety of selected data subsets, going beyond previous limitations due to linear estimation models.


CGV Colloquium – Friday April 13th

You are cordially invited to attend our next Computer Graphics and Visualization (CGV) Seminar/ Colloquium, which will be held on: Friday, April 13th, 2018, 15:45-16:45h, at EWI-Lecture Hall Pi. The programme features a guest talk.

Presenter: Dr. R.C. Lindenbergh
Assistant Professor
TU Delft, Dept. of Geoscience & Remote Sensing

Title: Robust feature extraction and change detection in large spatial point clouds

Abstract: Laser scanning is an efficient method to sample our urban and natural environment. LIDAR systems on tripods, drones, cars, drones and planes are able to collect billions of 3D points in a few hours. What remains challenging is to extract valid metric information from these points clouds in a time that matches the acquisition time. In the presentation first issues with these point clouds will be discussed, followed by example methods to extract metric information on e.g. trees, traffic signs or tunnels in a robust and computationally efficient way.

CGV Colloquium – Friday March 16th

You are cordially invited to attend our next Computer Graphics and Visualization (CGV) Seminar/ Colloquium, which will be held on: Friday, March 16th, 2018, 15:45-16:45h, at EWI-Lecture Hall Pi. The programme features a MSc graduation project midterm presentations.

Presenter: Niels van der Veen

Title: A paint-based approach for optimal lighting design in real scenes

Abstract: Light design is a computational expensive task, commonly done using Computer-aided design (CAD) software in a virtual scene. The designer places and tunes the virtual light sources and, yet the virtual environment is ideal for physically correct light tracing, the costly simulation might not provide the desired impression in the real scene. Moreover, the chosen light placement is not necessarily optimized. In this work we capture light behavior from real scenes as well as 3D scene properties and use this information to recreate different lighting designs. The results approximates physical correctness while visualizing the illumination on the real scene in a more time-efficient way. To make the design process more intuitive, the user paints the desired light properties instead of placing the light sources. The system attempts to find the optimal positions and parameters of the light sources in the scene to reflect the current design. Constraints such as number of light sources, emission profiles and external light information can also be specified.

CGV Colloquium – Friday March 2nd

The meeting on March 2nd is scheduled from 15:45-16:45 in EWI lecture hall Pi. The programme features a MSc graduation project midterm presentations.

Presenter: Bastiaan Grisèl

Title: Interactive analysis of 3D embeddings in Virtual Reality

Abstract: Developments in algorithm design and computing power have enabled dimensionality reduction algorithms to run in real-time. While embedding data in three dimensions can lead to a more faithful representation of a dataset when compared to embedding in two dimensions, embeddings are often visualised in 2D (on computer screens) with limited possibilities for interaction. Virtual Reality (VR) makes it possible to visualise embeddings in stereo 3D and interact with them using VR motion controllers, enabling the user to interact with the algorithm as it evolves and develop an understanding of both the algorithm and the dataset. This research uses a well-known dimensionality reduction algorithm called t-SNE and aims to provide the user with virtual tools to work with the algorithm to generate more powerful embeddings and better understand high-dimensional datasets.

CGV Colloquium – Friday February 2nd

You are cordially invited to attend our next Computer Graphics and Visualization (CGV) Seminar/ Colloquium, which will be held on:

Friday, February 2nd, 2017, 13:45-15:45h, at EWI-Lecture Hall K.

The program features the following two presentations:

Presentation 1:

Presenter: Yin Yunchao

Title: Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning

Abstract: Remarkable progress has been made in image recognition, primarily due to the availability of large-scale annotated datasets and deep convolutional neural networks (CNNs). CNNs enable learning data-driven, highly representative, hierarchical image features from sufficient training data. However, obtaining datasets as comprehensively annotated as ImageNet in the medical imaging domain remains a challenge. There are currently three major techniques that successfully employ CNNs to medical image classification: training the CNN from scratch, using off-the-shelf pre-trained CNN features, and conducting unsupervised CNN pre-training with supervised fine-tuning. Another effective method is transfer learning, i.e., fine-tuning CNN models pre-trained from natural image dataset to medical image tasks. In this paper, we exploit three important, but previously understudied factors of employing deep convolutional neural networks to computer-aided detection problems. We first explore and evaluate different CNN architectures. The studied models contain 5 thousand to 160 million parameters, and vary in numbers of layers. We then evaluate the influence of dataset scale and spatial image context on performance. Finally, we examine when and why transfer learning from pre-trained ImageNet (via fine-tuning) can be useful. We study two specific computer-aided detection (CADe) problems, namely thoraco abdominal lymph node (LN) detection and interstitial lung disease (ILD) classification. We achieve the state-of-the-art performance on the mediastinal LN detection, and report the first five-fold cross-validation classification results on predicting axial CT slices with ILD categories. Our extensive empirical evaluation,CNN model analysis and valuable insights can be extended to the design of high performance CAD systems for other medical imaging tasks.

Presentation 2:

Presenter: Dirk Schut

Title: Automatic Initialization for US CT Registration During Liver Tumor Ablations

Abstract: Ablation is a medical procedure where a needle has to be inserted into a tumor. To guide the needle Ultrasound(US) imaging is used which shows the needle position in real time. However small tumors are often not visible on US images. Therefore a CT scan is acquired before the intervention. To make the information from the CT scan available during the intervention, the scans have to be aligned in such a way that the same parts of the body are visible in the same positions in both scans. To find the relative orientation between the scans, this technique tries to detect and match blood vessels and the liver surface while also taking into account that the US scanner should be on the skin of the patient. The technique is being developed specifically to find solutions over a wide search space, and to be robust to segmentation errors.

CGV Colloquium – Tuesday March 15th

You are cordially invited to attend our next Computer Graphics and Visualization (CGV) Colloquium, which will be held on Tuesday March 15, 2016, 14:00-15:00, in the Vassiliadis zaal (HB10.230).

  • Dr. Amir Vaxman, Utrecht University
      • Title – Directional Field Synthesis, Design, and Processing


    • Abstract – Directional fields on discrete surfaces and in volumes are key components of geometry processing. Many applications make use of such fields, among which are remeshing, surface parametrization (texture mapping), texture synthesis, fluid simulation, and many more. I will present the challenges and the limitations in the design and the analysis of such fields, and focus on novel ways to compute them.

CGV Colloquium – Thursday July 16th

You are cordially invited to attend our next Computer Graphics and Visualization (CGV) Colloquium, which will be held on Thursday July 16, 2015, 15.45-17.20, in the Vassiliadis zaal (HB10.230). The program this month features the following speakers:

  • Panchamy Krishnan
    • Title – Supervised learning for measuring hip joint distance in digital X-ray images
    • Abstract – Osteoarthritis is a degenerative joint disease which is hard to measure objectively as the diagnosis differs from surgeon to surgeon.  Hip X-rays are used to diagnose this disease by measuring several characteristic features of the image, mainly the joint distance between the femoral head and acetabular cup.  Joint distance reduction is a clear sign of OA (it is a symptom of cartilage disappearance). This metric involves segmentation of the femur and acetabulum in x-rays, a challenging task because of contrast variations as well as external factors like anatomical and pose-variation. A multi-scale approach based on Machine Learning is proposed here providing a robust segmentation by detecting landmarks along the edges of the bone. The labelled landmarks are then used to determine the joint distance in several locations along the hip joint. The learning is supervised using manually annotated landmarks. The impact of landmark selection is studied in detail in this paper. The landmark detection is further refined using Active Shape Model (ASM) and gradient profiling.
  • Bas Dado
    • Title Compression of voxelized scenes using colored DAGs
    • Abstract – Voxels are great alternative for triangle-meshes. No texture and bump-mapping techniques are necessary to capture fine details, and rendering by means of raycasting is relatively cheap. However, a big dowside of voxels is the large memory footprint, even when a Sparse Voxel Octree (SVO) is used. Directional Acyclic Graphs can be used to reduce this problem but don’t allow for storing materials. We present a technique, based on the DAG compression, to efficiently store the voxel data. The presented technique is smaller than a standard SVO for all tested scenes in high resolution.
  • Kevin Allain
    • Title – Enhancing document triage process using multi layer visualization tool
    • Abstract The European Patent Office is an international organisation that is charged with granting patents for applications sent to their offices. To do so, the examiners have to verify if the claims of the application are indeed new or not, and thus perform a state of the art review. The tools currently used at the EPO return a list of patents that might match the keywords entered by the examiner, but it provides a very poor visualization of the results and document triage is a very cumbersome process. We work on a visualization of all the results from a search query to increase the document triage process, by showing data of all the results at once, offering several levels of details for the examiner to determine the patents that might not be relevant.

As a reminder, all CGV MSc students (both seminar and thesis project) are expected to attend our monthly colloquium series. All other interested colleagues are more than welcome, so feel free to disseminate this announcement.