Welcome to IPI, the Image Processing and Interpretation Research Group of the department TELIN of the Faculty of Faculty of Engineering and Architecture at Ghent University (Universiteit Gent).
IPI researchers conduct state of the art research in the field of digital image and video processing for a wide range of applications. Our research covers computer vision, sensor fusion, remote sensing, image reconstruction and enhancement, 3D image and video enhancement and synthetic view generation, and several other related areas. We apply our technology to applications such as autonomous vehicles, drone and intelligent surveillance, agricultural and industrial inspection, (bio)medical imaging, consumer multimedia, and art.
Our group currently counts more than 40 researchers. You can find the full list of our team here. Our senior members are:
If you are interested in joining our group as a doctoral student, please visit the following page in English or in Dutch. Spontaneous applications are always welcome. Open positions are listed under the Vacancy tab on the main menu.
IPI is a core research group of imec.
Several of our members are associated with the UGent UAV Research Center and the UGent Artificial Intelligence consortium. IPI is the leader of the Intelligent Information Processing valorisation consortium I-KNOW and participates in the Hybrid Computed Tomography valorization consortium HyCT.
IPI actively engages in collaborative research with other institutes and companies in the context of National and European projects. We are currently active in the following collaborative projects:.js-id-running
The SafeNav maritime safety project promises a path towards safer and more secure navigation for the navigator on the bridge today and then moving towards remote-operated and autonomous shipping. One key aspect to boost maritime safety is accurate and efficient detection and tracking of vessels and floating objects as well as marine mammals, in order to avoid navigational hazards such as collisions and subsequent damages to ships, crew members and the marine environment.
In SafeNav, IPI will use innovative sensor setups, including cameras to solve the main challenge = to improve the detection performance in difficult conditions: distant or semi-submerged marine animals or containers, waves crests and sun glitters, poor weather conditions.
EU-HORIZON, 9/2022 - 8/2025
The SeaDetect project, part of Europe's LIFE initiative, aims to halt the biodiversity loss due to collisions between ships and cetaceans by implementing and developing new technologies. To considerably reduce this risk of collision and protect marine life and biodiversity, the SeaDetect project aims to develop two innovative, complementary systems. The first is a detection system to be deployed on ships composed of multiple highly sensitive sensors, of which the data will be fused and processed with artificial intelligence in order to detect cetaceans up to 1km. The second is a network of Passive Acoustic Monitoring (PAM) buoys that will detect and triangulate the position of cetaceans in real-time in order to prevent collision for all vessels in usual maritime roads.
IPI's role in the project is to develop novel detection algorithms based on raw data fusion to improve the detection capabilities of the on-board systems.
EU-LIFE, 9/2022 - 8/2026
Holographic Skeletons for Wrist Surgery: The goal of HoloWrist is to use augmented reality to accurately show the location of a patient's wrist bones during surgery. This will be done by creating a hologram of the patient's wrist bones (e.g. from their CT scan) and using augmented reality headsets (e.g. Microsoft's HoloLens) to display the hologram on the patient's wrist.
IPI's focus is on motion tracking to ensure the hologram is aligned to the patient throughout the surgery.
FWO, 1/2022 – 12/2024
Future apt LIVING Lab for Autonomous Public Transport. LivingLAPT will deliver sustainable driver-less shuttle/logistics services among various European cities by phasing out the need for safety drivers in shuttles and moving towards remote operators who overlook a number of services simultaneously.
IPI will evaluate the safety near autonomous public transport. This applied research builds on our sensor fusion technology whose ongoing development is co-financed by the Flanders AI research program.
EIT Urban Mobility, 1/2022 - 12/2022
The goal of VISION2REUSE is to demonstrate the potential of smart cameras for the automatic monitoring of the quality of reusable packaging in the food and packaging industry. Based on these camera technologies and state-of-the-art machine learning, it will be measured in an accurate and fast way whether the packaging material in question is still suitable for a new reuse cycle or whether it should go to a dedicated end-of-life stream (e.g. recycling).
REACT-EU EFRO, 1/2022 - 12/2023
Framework of Key Enabling Technologies for Safe and Autonomous Drones
IPI contributes to a novel framework of key enabling technologies for safe and autonomous drones. We focus on hyperspectral imaging from manually flown drones for inspection of offshore turbines structure to detect imperfections, such as corrosion deterioration of paint.
ECSEL JU, 10/2019 – 1/2023
Demand for image sensors in automobiles, the Internet of Things, medicine or security and surveillance applications is challenging businesses to improve the performance of their integrated systems. EXIST is developing breakthrough image sensors that will expand the functionality of future vision systems.
ECSEL JU, 5/2015 - 12/2018
NextPerception aims to develop next generation smart perception sensors and enhance the distributed intelligence paradigm to build versatile, secure, reliable, and proactive human monitoring solutions for the health, wellbeing, and automotive domains
IPI investigates cooperative sensor fusion in support of safety and comfort at road intersections especially for vulnerable road users such as pedestrians and bikers
ECSEL JU, 5/2020 – 4/2023
PANORAMA will deliver solutions for applications in medical imaging, broadcasting systems and security & surveillance, all of which face similar challenging issues in the real time handling and processing of large volumes of image data.
ENIAC JU, 4/2012 - 12/2015
The SONOPA project - SOcial Networks for Older adults to Promote an Active Life - employs technologies to develop an end-to-end solution for stimulating and supporting activities at home.
EU, 5/2013 - 4/2016
The VIL project aims to improve print quality, reduce waste, and cut the cost of additive metal manufacturing
ICON project, 4/2020 - 3/2022
This project develops tools for X-ray imaging of dynamic processes in materials, with the goal of helping materials scientists to develop better and more sustainable materials.
IPI's focus is on developing algorithms capable of handling large 3D datasets including research on GPU processing, (ROI) CT reconstruction, and efficient optimization algorithms with the emphasis on huge amounts of data.
FWO-SBO, 1/2018 – 12/2022
iPlay: Interactive sports platform for comprehensive, 3D monitoring of athletes, 2017-2019
ARIA: Augmented Reality for Industrial Maintenance Procedures, 2016-2018
BAHAMAS: A toolset for the processing, compression and analysis of big data in life and materials science applications, 2015-2016
HD2R: Creating Images with Higher Dynamic Range and Richer Colors for Cinemas and Living Rooms, 2015-2017
wE-MOVE: Games to improve children’s rehabilitation and fitness level, 2015-2016
GIPA: Laying the foundation for a generic, state-of-the-art augmented reality (AR) platform, 2014-2015
FIAT: Unlocking the potential of ‘functional imaging’ to quantify tumor response to treatment earlier and more accurately, 2014-2015
EMDAS (Autonomous vehicles), 2015-2016
3DLicorneA, Brussels Institute for Research and Innovation, 2015-2018
Groundbreaking artificial intelligence research enabling a meaningful impact on people, industry and society. IPI researches real-time and power-efficient AI in the edge for various applications.
National project (Flemish EWI), 7/2019 – present
Researchers in ACHIEVE are designing highly integrated hardware-software components for the implementation of ultra-efficient embedded vision systems as the basis for innovative distributed vision applications
For IPI, the first goal of this project is to design algorithms for distributed multiple targets tracking through a decentralized approach. The second goal is to improve object detection and tracking using a multi-sensor approach. Thermal cameras have promising potential in surveillance applications, especially when combined with optical cameras. The third goal of the project is to provide solutions for behaviour analysis and action recognition. The research will use high-level analysis to automatically determine which cameras observe the same or similar action, such as pedestrians waiting to cross the street. Deep learning is a promising approach.
H2020-MSCA-ITN, 10/2017 – 9/2021