âSignal Processing in the AI eraâ was the tagline of this yearâs IEEE International Conference on Acoustics, Speech and Signal Processing, taking place in Rhodes, Greece.
In this context, Brent de Weerdt, Xiangyu Yang, Boris Joukovsky, Alex Stergiou and Nikos Deligiannis presented ETRO’s research during poster sessions and oral presentations, with novel ways to process and understand graph, video, and audio data. Nikos Deligiannis chaired a session on Graph Deep Learning, attended the IEEE T-IP Editorial Board Meeting, and had the opportunity to meet with collaborators from the VUB-Duke-Ugent-UCL joint lab.
Featured articles:
- De Weerdt, B. et al., âDesigning Transformer Networks for Sparse Recovery of Sequential Data Using Deep Unfoldingâ (https://ieeexplore.ieee.org/abstract/document/10094712)
- Yang X. et al., âRelevance Propagation through Deep Conditional Random Fieldsâ (https://ieeexplore.ieee.org/abstract/document/10095075)
- Stergiou A. et al., âPlay it back: Iterative attention for audio recognitionâ (https://ieeexplore.ieee.org/abstract/document/10096532, developed at the University of Bristol)
The paper entitledâ Novel Multi-Parametric Sensor System for Comprehensive Multi-Wavelength Photoplethysmography Characterizationâ, published in the journal MDPI SENSORS in 2023, coauthored by: J.L. Cause, Ă. SolĂ©-Morillo, B. Da Silva, J. GarcĂa-Naranjo, and J. Stiens was awarded with the first prize of the provincial council of scientific health societies of Santiago de Cuba
The I Love Science Festival at Tour & Taxis in Brussels on October 13-15 was a great success, drawing over 150000 science and technology enthusiasts of all ages. ETRO.RDI enchanted attendees with interactive exhibits, including light-based physiological readings, acoustic camera art, a crypto escape room challenge, and an AI-driven urban climate model.
For those who missed out on this year’s event, mark your calendars for the next I Love Science Festival, and be sure to check out ETRO.RDI’s booths.
Hiva Houshyar participated in the final pitch event of the FARI AI Accelerator and presented her business idea and her pitch was selected as âBest Pitchâ by the jury! đ
Her project, BB-GO, is building a navigation platform tailored to wheelchair users, focusing on personalised routing and urban accessibility. The vision is a world where wheelchair users can explore their city with the same confidence as anyone else.
Want to help shape BB-GO or link us to public authorities? Get in touch via Johan.Stiens@vub.be or Seyedeh.Hiva.Houshyar.Yazdian@vub.be
On November 14 2022 at 17.00, SĂ©golĂšne Rogge will defend her PhD entitled â’Depth estimation in multiview light field camera systemâ.
Everybody is invited to attend the presentation in room D.2.01.
In this research, we went through the main stages to render a 3D scene in 6 Degrees of Freedom: data acquisition, point cloud or depth map estimation, surface reconstruction and view synthesis rendering.
We generated datasets, some of them computer-generated using Blender, and some of them real scenery for which we built two acquisition rigs. On the first one we could put any type of camera â RGB or Time-of-Flight â which could then be moved in space in X, Y or Z direction thus sampling the scene anywhere withing a cube meter; the second one, more rigid, holding an array of 3-by-3 Light Field cameras. The acquired data was used to devise some depth estimation algorithms based on multi stereo matching algorithms improved with deep learning techniques. We also worked on the triangulation of a fast laser dot moving through the scene. We proved that the resulting depth map from one light field camera can be improved by using neighboring cameras while increasing the parallax. As each of the generated depth maps can be reprojected in space to form a point cloud, we implemented an improved a registration algorithm to put multiple point clouds together, enforcing the 3D structure of the scene. Finally, we rendered scenes on two different devices: a head mounted display and an holographic display. To render a point cloud in real time within an oculus, we stored it using an efficient data structure and optimized the rendering time using sub samples of the point cloud selected using level-of-detail based on the distance between the user and the various parts of the scene, and frustum culling. The visual comfort was brought to the user by the means of splatting techniques to simulate the surfaces of the scene. To render a scene on an holographic screen, we first captured it from different view points with light field cameras, then estimated the depth to be able to synthesize views in between, and use them as input to display on the screen.
Our work achieved state-of-the-art results, in particular in depth estimation for light field images and point clouds registration, and was published in various journals and conferences. It also led to multiple contributions in the Moving Picture Experts Group.
PROJECT: INTOWALL: detection of leaks and isolation in walls
Our buildings generate 35% of the CO2-emissions and 40% of the energy use. 75% of our buildings need to be energetically renovated. In order to do so, one needs to know what the status is of the current isolation, and if there are any water leaks. The Vrije Universiteit Brussel researches with a consortium of partners towards a unique, patented technique to look into the walls without breaking them. With a compact and mobile radar system you can “read” your walls. This project is part of the Smart Hub Cleantech, climate ambitions of the province and the communes.
Partners: Vrije Universiteit Brussel i.s.m. WTCB, Green Energy Park, BAM, ING, Flux50 en Alter Reim.
The Biomedical Engineering Master @ VUB accepts students with a bachelor or a Master in Engineering.
In case you do not have a full background in biomedical engineering, we consider you will need to perform a preparatory program consisting in several courses defined in a personalised study program for you.