Matting using a known background and a chroma-key minimization scheme

In this paper, we investigate the problem of segmenting the foreground objects from the known background. The target application is a setting where a large display serves as the backdrop for a scene. The method proposed in this paper solves this problem in two steps. We try to separate the foreground and the background with the modified...

Quantifying the effect of woody vegetation on the wave loads on a dike using remote sensing: Large scale physical model tests

It is already acknowledged that Nature-based Solutions can be used to attenuate waves, however it is still uncertain to what extent the vegetation can contribute to decreasing the flood risk. So far mainly small-scale tests have been performed to quantify wave attenuating properties of vegetation. To quantify the effect of more extreme wave...

An LC-to-camera communication system with ambient light

The current wireless networks can face congestion issues due to the increasing number of digital devices. One way to overcome this is to establish communica-tion at a different range of frequencies, specifically in visible light. Most studies in Visible Light Communication (VLC) systems use active light sources like LEDs for transmission, but...

Light studio for IDE students: Design of the Light studio for IDE students for professional product photography

While following courses at Industrial Design Engineering (IDE), students learn different steps of the design process. Little attention is paid to the last step of presenting the created product resulting in unprofessional photographs. The light studio is the developed concept and solution for this problem.<br/><br/>A dome-shaped structure with...

A Matter of Perspective

This thesis proposes the construction of three temporary pavilions at Place Francois Mitterrand in Lille, France. The pavilions will be part of the event “Lille World Design Capital” of 2020.<br/>“Everything is a matter of perspective”. Place Francois Mitterrand, the public core of the 1989’s Euralille Masterplan by OMA, is seen by many as a...

Sensor Data Fusion of Lidar and Camera for Road User Detection

Object detection is one of the most important research topics in autonomous vehicles. The detection systems of autonomous vehicles nowadays are mostly image-based ones which detect target objects in the images. Although image-based detectors can provide a rather accurate 2D position of the object in the image, it is necessary to get the accurate...

Deep End-to-end Network for 3D Object Detection in the Context of Autonomous Driving

Nowadays, autonomous driving is a trending topic in the automotive field. One of the most crucial challenges of autonomous driving research is environment perception. Currently, many techniques achieve satisfactory performance in 2D object detection using camera images. Nevertheless, such 2D object detection might be not sufficient for autonomous...

Tracking Location and Orientation of Multiple Group Housed Rodents

Recent technological advancements have made it possible to study complex social behaviors in rodents using automated observations. The Neuromate project of the Erasmus Medical Center and Delft University of Technology aims to expand the research possibilities with this technology by enabling closed-loop neuro-stimulation and observation in group...

Radar-guided Monocular Depth Estimation and Point Cloud Fusion for 3D Object Detection

Multi-class road user detection using the next- generation, 3+1D (range, azimuth, elevation, and Doppler) radars has been shown feasible, thanks to the increased density of their point clouds and the inclusion of elevation information. However, object detection networks using LiDAR (64-layer) point clouds still dominate the performance metrics....

VidCNN - Learning Blind Video Denoising

We propose a novel Convolutional Neural Network (CNN) for Video Denoising called VidCNN, which is capable to denoise videos without prior knowledge on the noise distribution (Blind). VidCNN is a flexible model, since it tackles multiple noise types, artificial and real. The CNN architecture uses a combination of spatial and temporal filtering,...

3D Object Detection For Intelligent Vehicles

This master thesis presents an experimental study on 3D person localization (i.e., pedestrians, cyclists)in traffic scenes, using monocular vision and Light Detection And Ranging (LiDAR) data. The performance of two top-ranking methods is analyzed on the 3D object detection KITTI dataset. In this evaluation, the effect of the Intersection over...