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
SafeNav will use innovative sensor setups, including cameras to solve the main challenge = to improve the detection performance in difficult conditions
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
Building Information Modelling (BIM) allows making elaborate, information-rich models of building designs. However, there is no easy way yet to couple these models to what is actually happening on-site, during a construction. The BoB project aims to create a 2-way link between BIM models and the actual building, improving building efficiency and avoiding costly errors
IPI researches camera networks and cross-modal 3D matching to link on-site camera images with 4D BIM models to estimate construction progress in highly challenging environments.
ICON project, 1/2022 – 12/2023
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
**ANALYST PV**: Integrated sensors and data analysis fault detection tools for photovoltaic plants, 2019–2021 (See the project results) **COSMO**: Designing, developing, and evaluating effective, personalized, and scalable AR and VR technologies for support and training in manufacturing operations, 2019-2021 **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
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
**EMDAS** (Autonomous vehicles), 2015-2016
**3DLicorneA**, Brussels Institute for Research and Innovation, 2015-2018
CHARAMBA aims to solve the problem of costly and labour-intensive sampling and chemical analysis of complex material/waste streams EIT RawMaterials, 1/2020 - 12/2021 Press release on the project results
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
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