autonomous vehicles

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.

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

IPI research on automotive vision featured in FierceElectronics

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

Prof. Wilfried Philips gives a keynote speech at AutoSens in Brussels

Keynote at AutoSens 2019