Computer Vision Laboratory
Welcome to the Computer Vision Laboratory (CVL), part of the Department of Electrical engineer at Linköping University.
The research at CVL covers a wide range of topics within artificial visual systems (AVS): computational imaging, detection, tracking and recognition, geometry, robot vision and autonomous systems and medical imaging.
The design of AVS has its roots in the modelling of the human visual system (HVS); an extremely challenging task that generations of researchers have attempted with limited success. Vision is a very natural capability and it is commonly accepted that about 80% of what we perceive is vision-based. Vision's highly intuitive nature makes it difficult for us to understand the myriad of problems associated with designing AVS, in contrast to sophisticated analytic tasks such as playing chess.
Thus AVS became a widely underestimated scientific problem, maybe one of the most underestimated problems of the past decades. Many AI researchers believed that the real challenges were symbolic and analytic problems and visual perception was just a simple sub-problem, to be dealt with in a summer project, which obviously failed. The truth is that computers are better than humans at playing chess, but even a small child has better generic vision capabilities than any artificial system. CVL aims at improving AVS capabilities substantially, driven by an HVS-inspired approach, as AVS are supposed to coexist with - and therefore predict actions of - humans.
Robot Vision and Autonomous Systems
Machines that learn to visually perceive their environment and to interact with it.
Medical Imaging and Image Analysis
Reconstruction of 3D points and motion trajectory of a vehicle moving in a traffic scenario.
Detection, Tracking and Recognition
Recognition and localization of objects in images and videos.
Modelling and correction of rolling shutter video.
- Computational imaging
- Detection, tracking and recognition
- Medical imaging
- Robot vision and autonomous systems
For more information on our research, see the publications and projects sections of the website. CVL also provides weekly seminars and teaching activities for undergraduate and graduate students, including the possibility for master students to be involved in state of the art research with their master thesis.
'He who loves practice without theory is like the sailor who
boards ship without a rudder and compass and never knows where he may
Leonardo da Vinci (1452-1519)
The papers "Beyond Correlation Filters: Learning Continuous Convolution Operators for Visual Tracking" (oral presentation) by Martin Danelljan, Andreas Robinson, Fahad Khan, Michael Felsberg and "Efficient Multi-Frequency Phase Unwrapping using Kernel Density Estimation" by Felix Järemo Lawin, Per-Erik Forssén, Hannes Ovrén were accepted at ECCV 2016.Two papers accepted at ICPR 2016.
The papers "Aligning the Dissimilar: A Probabilistic Method for Feature-Based Point Set Registration" by Martin Danelljan, Giulia Meneghetti, Fahad Khan, Michael Felsberg and "Deep Motion Features for Visual Tracking" by Susanna Gladh, Martin Danelljan, Fahad Khan, Michael Felsberg were accepted at ICPR 2016.Three papers accepted at IV 2016
The paper "Visual Autonomous Road Following by Symbiotic Online Learning" by Kristoffer Öfjäll, Michael Felsberg and Andreas Robinson, the paper "Evaluating visual ADAS components on the COnGRATS dataset" by Daniel Biedermann, Matthias Ochs and Rudolf Mester, and, the paper "Keypoint Trajectory Estimation Using Propagation Based Tracking" by Nolang Fanani and Rudolf Mester were accepted at the Intelligent Vehicles Symposium 2016.Paper accepted at SSIAI 2016
The paper "Propagation based tracking with uncertainty measurement in automotive application" by Nolang Fanani and Rudolf Mester was accepted at the Southwest Symposium on Image Analysis and Interpretation 2016.Paper accepted at CRV 2016
The papers "Adaptive Decontamination of the Training Set: A Unified Formulation for Discriminative Visual Tracking" and "A Probabilistic Framework for Color-Based Point Set Registration" by Martin Danelljan et al. were accepted at CVPR 2016.Organizing CAIP 2017
Michael Felsberg, Norbert Krüger (Odense), and Anders Heyden (Lund) will organize the next International Conference on Computer Analysis of Images and Patterns, CAIP 2017.Journal paper accepted: Journal of Field Robotics
The paper Highly accurate attitude estimation via horizon detection has been accepted in the Journal of Field Robotics.ICCV 2015 paper accepted
The paper Learning Spatially Regularized Correlation Filters for Visual Tracking has been accepted at ICCV 2015.Journal paper accepted: IEEE transaction on Image processing (TIP)
The paper Recognizing Actions Through Action-Specific Person Detection has been accepted in IEEE transaction on Image processing (TIP).Journal paper accepted: Frontiers in Robotics and AI
The paper Unbiased decoding of biologically motivated visual feature descriptors has been accepted for the speciality section on Vision Systems Theory, Tools and Applications.Winner of OpenCV Challenge in Tracking!
CVL team wins the OpenCV State of the Art Vision Challenge in Tracking. Team members: Martin Danelljan, Gustav Häger, Fahad Shahbaz Khan, Michael Felsberg.Visual Object Tracking Challenge at ICCV 2015
In a collaboration with Termisk Systemteknik, a new dataset for benchmarking tracking algorithms in thermal IR sequences has been produced. The paper "A Thermal Object Tracking Benchmark" has been accepted at AVSS 2015.WASP: 11 years program launched
We have released a new dataset that contains wide-angle rolling shutter video (GoPro sports camera) with corresponding gyroscope measurements.Erik Ringaby nominated for Best Nordic Thesis
The thesis of Erik Ringaby from CVL has been selected as one of two Swedish theses for consideration of the the Best Nordic Thesis Prize 2013-2014. The winner will be announced at the SCIA 2015 conference in June.CVL featured in ICRA promo video
The paper: Gyroscope-based Video Stabilisation with Auto-Calibration, by Hannes Ovrén and Per-Erik Forssén, is featured in the ICRA 2015 promotional video.
The paper will be presented at the ICRA 2015 conference in May.
The paper: "Robust Stereo Visual Odometry from Monocular Techniques" by Mikael Persson et al. has been accepted at the 2015 IEEE Intelligent Vehicles Symposium (IV2015). The method (cv4x) has been ranked first on the KITTI odometry benchmark among vision based methods until 2015-03-30.PhD defense for Freddie Åström
Freddie Åström successfully defended his PhD today. The thesis is available for download here.Four papers accepted at SCIA 2015
The papers submitted by first authors Giulia Meneghetti, Amanda Berg, Fahad Khan, and Martin Danelljan have been accepted at the Scandinavian Conference on Image Analysis (SCIA 2015), Copenhagen.Media coverage of EU project
Senast uppdaterad: 2015-05-25