Funded

BoB

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

HoloWrist

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

LivingLAPT

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

Past ICON projects

**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

VISION2REUSE

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

Past National Projects

**AVCON**, 2018-2019 **EMDAS** (Autonomous vehicles), 2015-2016 **3DLicorneA**, Brussels Institute for Research and Innovation, 2015-2018

CHARAMBA

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

Comp4Drones

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 – 9/2022

NextPerception

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

Vision-in-the-loop

The VIL project aims to improve print quality, reduce waste, and cut the cost of additive metal manufacturing ICON project, 4/2020 - 3/2022

MoCCha-CT

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

Flanders AI

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 – 6/2022

ACHIEVE

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