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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.

Research Areas

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.

Computational Imaging

Modelling and correction of rolling shutter video.

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 cast.'
Leonardo da Vinci (1452-1519)


CVL is co-organizing SSDL 2017

Michael Felsberg and Per-Erik Forssén are co-organizing the First Swedish Symposium on Deep Learning, SSDL 2017 which takes place in June, at KTH in Stockholm.

Paper accepted at CVPR 2017!

The paper "ECO: Efficient Convolution Operators for Tracking" by Martin Danelljan, Goutam Bhat, Fahad Khan, Michael Felsberg was accepted at CVPR 2017.

Presentation at GTC 2017

Michael Felsberg will give a presentation at GTC 2017.

New PhD Thesis from CVL

Today Marcus Wallenberg successfully defended his PhD thesis Embodied Visual Object Recognition. Congratulations Marcus!

Best paper award at ICPR 2016!

For the paper "Deep Motion Features for Visual Tracking" by Susanna Gladh, Martin Danelljan, Fahad Khan, Michael Felsberg in the "Computer Vision and Robot Vision" track.

Conference paper accepted: SPIE DSS

The paper "Three-dimensional hyperspectral imaging technique" by Jörgen Ahlberg, David Bergström, Tomas Chevalier, Joakim Rydell, Martin Svensson and Ingmar Renhorn has been accepted for oral presentation at Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXIII at the SPIE Defense+Security Symposium 2017.

CVL Kinect depth decoding in libfreenect2

The CVL depth decoding algorithm from ECCV'16 is now merged into the main libfreenect2 tree. Check it out if you want an extended range (up to 18.75m) or better performance outdoors.

Journal paper accepted: TGRS

The journal paper "Optimizing object, atmosphere, and sensor parameters in thermal hyperspectral imagery" by Jörgen Ahlberg was accepted for publication in IEEE Transactions on Geoscience and Remote Sensing.

Journal paper accepted: TPAMI!

The journal paper "Discriminative Scale Space Tracking" by Martin Danelljan, Gustav Häger, Fahad Khan, Michael Felsberg of the VOT2014 winning DSST tracker was accepted at Transactions on Pattern Analysis and Machine Intelligence (TPAMI).

Journal paper accepted: Ecology and Evolution

The journal paper "Emlen funnel experiments revisited: methods update for studying compass orientation in songbirds" by Giuseppe Bianco, Mihaela Ilieva, Clas Veibäck, Kristoffer Öfjäll, Alicja Gadomska, Gustaf Hendeby, Michael Felsberg, Fredrik Gustafsson and Susanne Åkesson was accepted at Ecology and Evolution.

Two papers accepted at ECCV 2016!

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.

Three 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, "Deep Motion Features for Visual Tracking" by Susanna Gladh, Martin Danelljan, Fahad Khan, Michael Felsberg, and "Learning Local Descriptors by Optimizing the Keypoint-Correspondence Criterion" by Nenad Markus, Igor Pandzic and Jörgen Ahlberg were accepted at ICPR 2016 as oral presentations.

Journal paper: PatRec

The journal paper "Enhanced analysis of thermographic images for monitoring of district heat pipe networks" by Amanda Berg, Jörgen Ahlberg and Michael Felsberg was accepted for publication in Pattern Recognition Letters.

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 paper "Improving Random Forests by correlation-enhancing projections and sample-based sparse discriminant selection" by Marcus Wallenberg and Per-Erik Forssén was accepted at CRV 2016.

Two papers at CVPR 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

CVL is involved in the organization of the 3rd Visual Object Tracking Challenge VOT2015 to be held in conjunction with the ICCV 2015.

Benchmark paper accepted at AVSS 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

LiU will host the Wallenberg Autonomous Systems Program (WASP), see LiU News (the featured image shows a snapshot from CVL's AMUSE dataset).

New dataset released

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.

Paper accepted at IEEE IV 2015

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

CVL is participating in the EU project CENTAURO, to be launched in April, but already covered in public media.

Earlier news

Senast uppdaterad: 2015-05-25