Overview Monocular visual odometry LIDAR based odometry Automotive occupancy mapping Object detection and tracking Obstacle detection based on 3D imaging 3D scene mapping Low level point cloud processing Multimodal sensor fusion High dynamic range video capture Real-time sensor data processing for autonomous vehicles using Quasar Monocular visual odometry Current consumer vehicle navigation relies on Global Navigation Satellite Systems (GNSS) such as GPS, GLONASS and Galileo.
Environmental perception systems for autonomousvehicles are often built using heterogeneous technologies thatoperate in a sequential manner. In the task of object trackingin particular, where the classical detector-tracker interactionis a serial …
Depth images generated by direct projection of LiDAR point clouds on the image plane suffer from a great level of sparsity which is difficult to interpret by classical computer vision algorithms. We propose a method for completing sparse depth images …
Image/video quality assessment
Overview Video and image quality assessment Content-aware video quality assessment Color differences Methodological considerations for subjective QA studies Video and image quality assessment Quality assessment (QA) consists of measuring the user’s subjective opinion of perceived image/video quality, the user’s quality preferences, or the utility of the images for a specific task. The goal of QA is to evaluate and compare imaging systems, and to help drive system design (e.
Topics in image and video restoration at imec-IPI-Ghent University Overview High Dynamic Range imaging Denoising of time-of-flight depth images and sequences Multicamera image fusion Non-local image reconstruction Multiframe superresolution Demosaicing Error Concealment Wavelet-based denoising of images Non-local means denoising of images Restoration of historical videos Joint removal of blocking artifacts and resolution enhancement High Dynamic Range Imaging Conventional display and image capture technology is limited to a narrow range of luminosities and images associated with such systems have been retroactively called Low Dynamic Range images(LDR).
Overview Foreground background segmentation for dynamic camera viewpoints Sensor networks and methods for wellness monitoring of the elderly Collaborative Tracking in Smart Camera Networks Distributed Camera Networks Multi Camera Networks Automatic analysis of the worker’s behaviour Foreground/background segmentation Immersive communication by means of computer vision (iCocoon) 3D reconstruction using multiple cameras Real-time video mosaicking Gesture Recognition Behaviour analysis Material Analysis using Image Processing Foreground background segmentation for dynamic camera viewpoints In video sequences, interesting objects can be separated from the background by comparing the current input to a background model.
Overview Focal Cortical Dysplasia (FCD) Detection in MRI WaVelocity - Cardiovascular Image Analysis Software Diffusion MRI data analysis and processing 3D Microwave tomography for breast tumor detection Shearlet regularization for compressive sensing MRI Parallel MRI+compressive sensing Robust Segmentation Methods for Aortic Pulse Wave Velocity Measurement Skeletonization and segmentation for cerebral vessel delineation Generalized profiling with application to arteriovenous malformation segmentation Segmentation of lung airways Denoising of medical images Skeletonization for best path calculation in 3-D MRI images of blood vessels Fast and memory-efficient 3D segmentation and morphology MRI segmentation of the developing newborn brain Medical image and video quality assessment Subjective QA in medical imaging Task-based QA using numerical model observers Task-based QA for interventional X-ray sequences DICOM calibration of medical stereoscopic displays Video latency in laparoscopic surgery Automatic plant phenotyping using image analysis Estimation of objects’ features in biological images Analysis of high-throughput screening of C.
Overview 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.
test Art work project This project includes interdisciplinary work between image processing specialists, mathematicians and art scholars on virtual restoration and analysis of art work. It is conducted in collaboration with Vrije Universiteit Brussel, Department of Art, Music and Theater Sciences of Ghent University, The Flemish Academic Center for Science and Arts (VLAC) of the Royal Flemish Academy (KVAB) and the Mathematics Department, Duke University, USA. Our case study is the Ghent Altarpiece or the Lam Gods, a polyptych, dated by inscription 1432, painted by Jan and Hubert van Eyck.