Sensor fusion

Autonomous Vehicles and Sensor Fusion

Topics Cooperative fusion for tracking of pedestrians from a moving vehicle Radar-Video sensor fusion LIDAR-Radar-Video sensor fusion Radar pedestrian detection using deep learning Multimodal vision 2D multi-modal video fusion for wide-angle environment perception Visible-thermal video enhancement for detection of road users Automotive High Dynamic Range (HDR) imaging Classic multi-exposure HDR reconstruction Intelligent HDR tone mapping for traffic applications Learning-based HDR video reconstruction and tone mapping Efficient multi-sensor data annotation tool Point-cloud processing Fast Low-level Point-cloud processing Point-cloud based Object detection and tracking Environment mapping and odometry Liborg - Lidar based mapping LIDAR based odometry Monocular visual odometry Automotive occupancy mapping Obstacle detection based on 3D imaging Real-time sensor data processing for autonomous vehicles using Quasar - demo video Cooperative fusion for tracking of pedestrians from a moving vehicle Autonomous vehicles need to be able to detect other road users and roadside hazards at all times and in all conditions.

Remote Sensing

Topics Hyperspectral Image Restoration Hyperspectral Multi-sensor Data Fusion Spatial Information Modelling Image classification in hyperspectral images Hyperspectral Image Restoration Despite advances in sensor technology, hyperspectral (HS) images are inevitably degraded by noise and blur, which can affect information retrieval and content interpretation. Using denoising and deblurring as a preprocessing tool will improve various post-processing tasks, e.g. classification, target detection, unmixing, etc. We propose a novel restoration algorithm for HS images. Our method first uses PCA to decorrelate the HS images and separate the information content from the noise. The first k PCA channels contain most information of the HS image, and the remaining B ? k PCA channels (where B is the number of spectral bands of HS image) mainly contain noise. If deblurring is performed on these noisy and high-dimensional B ? k PCs, then it will amplify the noise of the data cube and cause high computational cost in processing the data, which is undesirable.

Watch the interviews of IPI professors Wilfried Philips & Jan Aelterman at AutoSens Brussels 2023

Listen to them discuss sensor fusion, sensors, weather and environmental conditions, and difficult corner cases

IPI professor Wilfried Philips discusses the latest trends in automotive sensing in an Autosens blog post

Thermal imaging to the rescue, radar advancing at rapid pace and handling the complexity of automotive sensor fusion

PhD defense of Martin Dimitrievski on April 25, 2023

Cooperative Sensor Fusion for Autonomous Driving

PhD defense of Xudong Zhao on March 28, 2023

Hyperspectral and LiDAR Data Fusion and Classification

MCM Lab Brainstorm for Innovation event at TELIN

Fuelling tomorrow's innovation in the field of naval mine countermeasures, in a responsible way. MCM Lab is a collaborative R&D network to bring together Belgian defense, industry and research organizations.

SafeNav: New EU collaborative innovation action to boost Safer Navigation at sea

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


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

CFP: Remote Sensing journal special issue 'Application of UAS-Based Spectral Imaging in Agriculture and Forestry'

IPI professor Hiep Luong is a Special Issue Editor. Deadline for manuscript submissions is 15 November 2022.

IPI research on cooperative sensor fusion featured in EOS Science Special on Innovation and Sustainability

Advanced sensor systems bring a future with zero road casualties

Sensor Fusion course at Autosens Academy

IPI contributes a course on Sensor Fusion to AutoSens Academy, the world’s leading community for ADAS and autonomous vehicle technology development

Webinar: The Future of Solar Site Management

IPI researcher Michiel Vlaminck and partners showcase the results of the icon Analyst-PV project with a webinar and article

Online Talk: Cooperative sensor fusion for detection and tracking

Watch IPI researcher ​​​​​​​David Van Hamme talk about Cooperative Sensor Fusion research

IPI research on automotive vision featured in FierceElectronics

Bringing pedestrian detection for autos to the next level: cooperative sensor fusion and automatic tone mapping

Two upcoming PhD defenses at IPI

Zhixin Guo (October 15) and Maarten Slembrouck (October 20)


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