AI

Autonomous Vehicles and Sensor Fusion

Topics Cooperative radar-video tracking of pedestrians from a moving vehicle Multimodal vision Radar pedestrian detection using deep learning Low level point cloud processing Object detection and tracking Liborg - Lidar based mapping LIDAR based odometry Automotive occupancy mapping High dynamic range video capture Monocular visual odometry Obstacle detection based on 3D imaging Cooperative radar-video tracking of pedestrians from a moving vehicle Click here for a video by IPI researcher David Van Hamme explaining Cooperative sensor fusion for detection and tracking Click here for an article by IPI researchers David Van Hamme and Jan Aelterman: I Can See Clearly Now! Advanced pedestrian detection using radar-video sensor fusion and automatic tone mapping Autonomous vehicles need to be able to detect other road users and roadside hazards at all times and in all conditions. No single sensor is dependable enough for this task, hence sensor fusion is required.

Intelligent surveillance and sensor networks

Topics Networked sensors Sensor networks and methods for wellness monitoring of the elderly Collaborative Tracking in Smart Camera Networks Distributed Camera Networks Multi Camera Networks 3D reconstruction using multiple cameras Real-time video mosaicking Scene and human behavior analysis Foreground background segmentation for dynamic camera viewpoints Foreground/background segmentation Automatic analysis of the worker's behaviour Gesture Recognition Behaviour analysis Immersive communication by means of computer vision (iCocoon) Material Analysis using Image Processing Sensor networks and methods for wellness monitoring of the elderly Addressing the challenges of a rapidly-ageing population has become a priority for many Western countries. Our aim is to relieve the pressure from nursing homes’ limited capacity by pursuing the development of an affordable, round-the-clock monitoring solution that can be used in assisted living facilities. This intelligent solution empowers older people to live (semi-) autonomously for a longer period of time by alerting their caregivers when assistance is required.

Real-Time Industrial Inspection

Topics Real-time monitoring in Additive Manufacturing Real-time monitoring in Additive Manufacturing In additive manufacturing, items are 3D printed layer-by-layer using materials like plastics, polymers, and metals. Unfortunately, instabilities in the printing process can produce defects like cracks, warping, and pores/voids within the printed item. Our goal at IPI is to develop computer vision systems that identify the creation of these defects in real time, then provide the 3D printer with sufficient information to intervene in a way that corrects, or avoids, the defect. Since these defects can occur over a very short amount of time (< 1 ms), our monitoring systems need to operate at very high speeds while also providing accurate results. Melt pool monitoring: GPU-based real-time detection of pore defects using dynamic features and machine learning Using high speed cameras and photodiodes (sampling rates > 20 kHz), we are exploring AI models that can highlight defect creation.

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

AI-Based traffic analytics for improved safety in smart cities

Ljubomir Jovanov will present at the AI4 Smart Mobility session during Trefdag Digitaal Vlaanderen on 25 November

IPI Additive Manufacturing Research Highlighted in Recent Youtube Video

Demonstration of a real-time monitoring system for 3D metal printing based on AI and active learning

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

IPI joins Industry Leaders in AI for Manufacturing Webinars

Brian Booth joined industry leaders earlier this year to speak on the use of AI in additive manufacturing workflows

Air quality equals quality of life. The challenge: better air-quality mapping. IPI research featured in imec report.

Flemish technology research on fine-grained air-quality monitoring available to be embraced by government, citizens and industry

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