Teaser

The Scandinavian Conference on Image Analysis (SCIA) is a biennial conference on computer vision, image analysis, and pattern recognition. It has been held since 1980 in the scandinavian countries Sweden, Denmark, Norway and Finland. In 2019, SCIA will return to Linköping University, Sweden, where the first conference was held in 1980. However, this time it will be in the nearby city of Norrköping, which hosts the Norrköping Campus of Linköping University.

The conference will be co-located with the Swedish Symposium on Deep Learning (SSDL), which takes place on June 10-11. For more information on SSDL, please see the symposium webpage.

Proceedings of the conference are now online: Springer Lecture Notes in Computer Science

SSBA LIU Springer LNCS IAPR

Gold sponsors:

Silver sponsors:

Program

Keynote speakers

Laura Leal-Taixe
  • IAPR keynote speaker: Laura Leal-Taixé
  • Professor, Technical University of Munich

  • Prof. Laura Leal-Taixé is leading the Dynamic Vision and Learning group at the Technical University of Munich, Germany. She received her Bachelor and Master degrees in Telecommunications Engineering from the Technical University of Catalonia (UPC), Barcelona. She did her Master Thesis at Northeastern University, Boston, USA and received her PhD degree (Dr.-Ing.) from the Leibniz University Hannover, Germany.

    During her PhD she did a one-year visit at the Vision Lab at the University of Michigan, USA. She also spent two years as a postdoc at ETH Zurich, Switzerland and one year at the Technical University of Munich. In 2017, she won the Sofja Kovalevskaja Award of 1.65 million euros from the presitgious Humboldt Foundation for her project "socialMaps".


  • Dynamic Scene Understanding - With or without time?
  • If you ask any student nowadays what tools to use to solve an image recognition task, the most popular answer will be Deep Learning. But the real-world is not static but rather dynamic, and therefore better represented by videos than by still images. It is still an interesting open question how to deal with the temporal redundancy of video frames: shall a Neural Network exploit it or ignore it?

    In this talk, I will explore both strategies, i.e., to actually exploit the redundancy in the content of nearby frames, or to ignore it.

    In the first work on multiple object tracking, I show how to obtain temporally coherent results while not using temporal information during training. This also alleviates the need for full video annotations. From our recent work on video super resolution, I will present our new temporal discriminator which works in a Generative Adversarial Network training scheme in order to create temporally coherent image details.



Lourdes Agapito
  • Lourdes Agapito
  • Professor, University College London

  • Lourdes Agapito holds the position of Professor of 3D Vision in the Department of Computer Science at University College London (UCL). Her research in Computer Vision has focused on the inference of 3D information from the video acquired from a single moving camera. While early research focused on static scenes, attention soon turned to the much more challenging problem of estimating the 3D shape of non-rigid objects (Non-Rigid Structure from Motion, NR-SFM) or complex dynamic scenes where an unknown number of objects might be moving, possibly deforming, independently. Prof. Agapito's research group investigates all theoretical and practical aspects of NRSFM: deformable tracking; dense optical flow estimation and non-rigid video registration; 3D reconstruction of deformable and articulated structure and dense 3D modelling of non-rigid dynamic scenes.


  • Capturing vivid 3D models of the world from video
  • As humans we take the ability to perceive the 3D world around us for granted. From an early age we can grasp an object by adapting our fingers to its 3D shape; or understand our own mother's feelings by interpreting her facial expressions. These tasks require some internal 3D representation of shape, deformations and motion. Building algorithms that can emulate this level of human 3D perception has proved to be an extremely hard task. In this talk I will focus on the acquisition of 3D models of deformable surfaces, such as human faces or bodies, using as input video sequences taken with a single consumer camera. There is now great short-term potential for commercial uptake of this technology. I will share how my research can empower business and society showing some applications to robotics and to AI-driven video synthesis.

  • Slides (restricted access) [PDF]



Fred Hamprecht
  • Fred Hamprecht
  • Professor, Heidelberg University
  • Visiting Professor, Uppsala University

  • Fred Hamprecht holds the Robert-Bosch endowed professorship for Image Analysis and Learning at Heidelberg University. His research interests lie in image processing and machine learning. His main focus is on the development of algorithms to solve interesting problems from the life sciences. Major applications include the tracing of all neurites in a brain, the tracking of all cells in a developing embryo, and quantitative analysis of high-throughput experiments. The group puts particular emphasis on the user-friendly training of such systems, and is actively developing open source libraries and programs such as ilastik. Prof. Hamprecht studied and earned his PhD at the Swiss Federal Institute of Technology (ETH), and became a Professor for Multidimensional Image Processing at Heidelberg University in 2001. He is a co-founder of the Heidelberg Collaboratory for Image Processing (HCI).


  • Signed graph partitioning: an important computer vision primitive
  • Perennial computer vision problems such as image partitioning, instance segmentation or tracking can be reduced to combinatorial graph partitioning problems.

    The majority of models developed in this context have relied on purely attractive interactions between graph nodes. To obtain more than a single cluster, it is then necessary to pre-specify a desired number of clusters, or set thresholds.

    A notable exception to the above is multicut partitioning / correlation clustering, which accommodates repulsive in addition to attractive interactions, and which automatically determines an optimal number of clusters. Unfortunately, the multicut problem is NP-hard.

    In this talk, I will characterize the combinatorial problem and discuss its representations in terms of node or edge labelings. I will discuss greedy algorithms that find approximate solutions, or even exact ones under certain conditions. One algorithm I will discuss is the "mutex watershed" which currently gives the best results on a connectomics challenge.

    Joint work with Steffen Wolf, Constantin Pape, Nasim Rahaman, Alberto Bailoni, Ullrich Koethe, Anna Kreshuk.



Schedule

Tuesday, June 11
11.45 - 13.00Registration and lunchThe lunch is sponsored by AIDA and SECTRA
13.00 - 13.15Opening
13.15 - 14.30Oral session 1Deep convolutional neural networks
14.30 - 15.00Poster spotlights 1
15.00 - 17.00Poster session 1, with coffeeOral session 1 & poster spotlights 1
17.00 - 17.45Keynote: Fred HamprechtSigned graph partitioning: an important computer vision primitive
18.00 - Dome demo, mingle, reception
Wednesday, June 12
09.00 - 10.15Oral session 2Feature extraction and image analysis
10.15 - 10.45Coffee break
10.45 - 12.00Oral session 3Medical and biomedical image analysis
12.00 - 13.00Lunch
13.00 - 13.45Keynote: Lourdes AgapitoCapturing vivid 3D models of the world from video
13.45 - 14.15Poster spotlights 2
14.15 - 16.15Poster session 2, with coffeeOral session 2 & 3 & poster spotlights 2
16.15 - 17.45Oral session 4Matching, tracking and geometry
19.00 - Conference dinner
Thursday, June 13
09.00 - 09.45IAPR keynote: Laura Leal TaixéDynamic Scene Understanding - With or without time?
09.45 - 10.15Poster spotlights 3
10.15 - 11.45Poster session 3 , with coffeeOral session 4 & poster spotlights 3
11.45 - 12.00The future of SCIA/Closing words
12.00 - 13.00Lunch


Papers

Oral session 1Session chair: Anders Heyden
Deep Multi-class Adversarial Specularity RemovalJohn Lin (CEA)*; Mohamed El Amine Seddik (CEA); Mohamed Tamaazousti (CEA); Youssef Tamaazousti (MIT CSAIL); Adrien Bartoli (Université Clermont Auvergne)
Predicting Novel Views Using Generative Adversarial Query NetworkPhong Nguyen (University of Oulu)*; Janne Heikkila (University of Oulu, Finland); Esa Rahtu (Tampere University); Lam Huynh ( University of Oulu)
CubiCasa5K: A Dataset and an Improved Multi-Task Model for Floorplan Image AnalysisAhti Kalervo (Aalto University)*; Juha Ylioinas (Aalto University); Markus Häikiö (CubiCasa Inc); Antti Karhu (CubiCasa Inc); Juho Kannala (Aalto University, Finland)
An efficient solution for semantic segmentation: ShuffleNet V2 with atrous separable convolutionsSercan Türkmen (University of Oulu, Finland)*; Janne Heikkila (University of Oulu, Finland)
Poster spotlights 1Session chair: Ewert Bengtsson
Unstructured Multi-View Depth Estimation Using Mask-Based Multiplane RepresentationYuxin Hou (Aalto University)*; Arno Solin (Aalto University); Juho Kannala (Aalto University, Finland)
Fine-Grained Wood Species Identification Using Convolutional Neural NetworksDmitrii Shustrov (Lappeenranta University of Technology); Tuomas Eerola (Lappeenranta University of Technology)*; Lasse Lensu (Lappeenranta University of Technology); Heikki Kälviäinen (Lappeenranta University of Technology); Heikki Haario (Lappeenranta University of Technology)
Filtering Specular Reflections by Merging Stereo ImagesMichael Plattner (FH OÖ Forschungs & Entwicklungs GmbH)*
Near Lossless JPEG Compression Based on Masking Effect of Non-Predictable Energy of Image RegionsMykola Ponomarenko (TUT)*; Karen Egiazarian (TUT, Tampere, Fnland)
Using a Robotic Arm for Measuring BRDFsRasmus Ahrenkiel Lyngby (Technical University of Denmark); Jannik Boll Nielsen ( Technical University of Denmark); Jeppe Revall Frisvad (Technical University of Denmark)*; Anders Bjorholm Dahl (Technical University of Denmark); Henrik Aanæs ( Technical University of Denmark)
Iris Identification in 3DFernand Cohen (Drexel University); Sowrirajan Sowmithran (Drexel University); Chenxi Li (Drexel University)*
Parametric Model-based 3D Human Shape and Pose Estimation from Multiple ViewsZhongguo Li (Lund University)*; Anders Heyden (Lund University); Magnus Oskarsson (Lund University)
Efficient Merging of Maps and Detection of ChangesGabrielle Flood (Lunds Tekniska Högskola)*; David Gillsjö (Lund University); Anders Heyden (LTH); Kalle Åström (Lund University)
Can SPHARM-based features from automated or manually segmented hippocampi distinguish between MCI and TLE?Michael Liedlgruber (University of Salzburg); Kevin Butz (Paracelsus Medical University); Yvonne Höller (Paracelsus medical University); Georgi Kuchukhidze (Paracelsus Medical University); Alexandra Taylor (Paraclesus Medical University); Aljoscha Thomschevski (Paracelsus Medical University); Ottavio Tomasi (Paracelsus Medical University); Eugen Trinka (Paracelsus Medical University); Andreas Uhl (University of Salzburg)*
Oral session 2Session chair: Gunilla Borgefors
Compressed Imaging at Long Range in SWIRDavid Gustafsson (Swedish Defence Research Agency (FOI))*; David Bergström (Swedish Defence Research Agency (FOI)); Carl Brännlund ( Swedish Defence Research Agency (FOI)); Andreas Brorsson ( Swedish Defence Research Agency (FOI))
Zonohedral Approximation of Spherical Structuring Element for Volumetric MorphologyPatrick Jensen (Danmarks Tekniske Universitet)*; Camilla Trinderup (Technical University of Denmark); Anders Bjorholm Dahl (Technical University of Denmark); Vedrana Andersen Dahl (Technical University of Denmark)
Image Invariants to Anisotropic Gaussian BlurJitka Kostková ( Institute of Information Theory and Automation, CAS)*; Jan Flusser (UTIA, Czech Academy of Sciences); Matěj Lébl (Institute of Information Theory and Automation, CAS)
Material-Based Segmentation of ObjectsJonathan Dyssel Stets (Technical University of Denmark); Rasmus Ahrenkiel Lyngby (Technical University of Denmark)*; Jeppe Revall Frisvad (Technical University of Denmark); Anders Bjorholm Dahl (Technical University of Denmark)
Oral session 3Session chair: Ingela Nyström
Fast Cross Correlation for Limited Angle Tomographic DataRicardo Sanchez (Max Planck Institute for Biophysics)*; Rudolf Mester (Goethe University Frankfurt); Mikhail Kudryashev (Max Planck Institute for Biophysics)
Sulcal and cortical features for classification of Alzheimer's disease and mild cognitive impairmentMaciej Plocharski (Aalborg University)*; Lasse Østergaard (Aalborg University)
On the Effectiveness of Generative Adversarial Networks as HEp-2 Image Augmentation ToolTomas Majtner (University of Southern Denmark)*; Buda Bajic (Faculty of Technical Sciences, University of Novi Sad); Joakim Lindblad (Centre for Image Analysis, Department of Information Technology, Uppsala University, Sweden); Natasa Sladoje (Centre for Image Analysis, Department of Information Technology, Uppsala University, Sweden); Victoria Blanes-Vidal (University of Southern Denmark); Esmaeil S. Nadimi (University of Southern Denmark)
Parameter Selection for Regularized Electron Tomography Without a Reference ImageYan Guo (Delft University of Technology)*; Bernd Rieger (Delft University of Technology)
Poster spotlights 2Session chair: Vedrana A. Dahl
Spectral-Spatial Hyperspectral Image Classification Using Cascaded Convolutional Neural NetworksGurbandurdy Dovletov (University of Duisburg-Essen)*; Tobias Hegemann (University Duisburg-Essen); Josef Pauli (University of Duisburg-Essen)
Unsupervised Feature Extraction -- a CNN-based ApproachDaniel Trosten (UiT The Arctic University of Norway)*; Puneet Sharma (UiT-The Arctic University of Norway)
Automatic detection of cervical vertebral landmarks for fluoroscopic joint motion analysisIda Marie Groth Jakobsen (Aa); Maciej Plocharski (Aalborg University)*
Alignment of Building Footprints Using Quasi-Nadir Aerial PhotographyDimitri Bulatov (Fraunhofer IOSB)*
Evaluation of Feature Detectors, Descriptors and Match Filtering Approaches for Historic Repeat PhotographyAnn-Katrin Becker (Universität Osnabrück)*; Oliver Vornberger (Universität Osnabrück)
Color Normalization of Blood Cell ImagesEmmy Sjöstrand (CellaVision)*; Jesper Jönsson (CellaVision)
Oral session 4Session chair: Heikki Kälviäinen
Combining Depth Fusion and Photometric Stereo for Fine-Detailed 3D ModelsErik Bylow (Lund University)*; Carl Olsson (Lund University, Sweden); Fredrik Kahl (Chalmers); Robert Maier (Technical University of Munich)
Camera localization by single view query using one circular targetDamien Mariyanayagam (IRIT)*; Pierre Gurdjos (IRIT, ENSEEIHT-INP, Toulouse); Sylvie Chambon (IRIT, ENSEEIHT-INP, Toulouse); Vincent Charvillat (IRIT, ENSEEIHT-INP, Toulouse)
Global Trifocal AdjustmentPatrik Persson (Lund University)*; Kalle Åström (Lund University)
A Robust Human Activity Recognition Approach Using OpenPose, Motion Features, and Deep Recurrent Neural NetworkFarzan Majeed Noori (University of Oslo)*; Benedikte Wallace (University of Oslo); Md Zia Uddin (UiO); Jim Torresen (University of Oslo)
Video Frame Interpolation via Cyclic Fine-Tuning and Asymmetric Reverse FlowMorten Hannemose (Technical University of Denmark)*; Janus Jensen (Technical University of Denmark); Gudmundur Einarsson (Oqton); Jakob Wilm (University of Southern Denmark); Anders Bjorholm Dahl (Technical University of Denmark); Jeppe Revall Frisvad (Technical University of Denmark)
Poster spotlights 3Session chair: Maciej Plocharski
Assessing Capsule Networks with Biased DataBruno Ferrarini (University of Essex)*; Shoaib Ehsan (University of Essex); Adrien Bartoli (Université Clermont Auvergne); Ales Leonardis (University of Birmingham); Klaus D McDonald-Maier (University of Essex)
Facial Emotion Recognition with Varying Poses and/or Partial Occlusion using Multi-stage Progressive Transfer LearningSherin Aly (Alexandria University)*
Weight Estimation of Broilers in Images using 3D Prior KnowledgeAnders Jørgensen (IHFood)*
Salient Object Detection With CNNs and Multi-scale CRFsYingyue Xu (University of Oulu)*; Xiaopeng Hong (Xi'an Jiaotong University); Guoying Zhao (University of Oulu)
Dimensionality Reduction for Visualization of Time Series and TrajectoriesPattreeya Tanisaro (University Osnabrueck)*; Gunther Heidemann (Institute of Cognitive Science, University of Osnabrück)
An RNN-based IMM Filter SurrogateStefan Becker (Fraunhofer IOSB)*; Ronny Hug (Fraunhofer Institute of Optronics, System Technologies and Image Exploitation (IOSB)); Wolfgang Hübner (Fraunhofer IOSB); Michael Arens (Fraunhofer IOSB)
Real-Time Tracking-by-Detection in Broadcast Sports VideosSigurdur Sverrisson (Ericsson AB)*; Volodya Grancharov (Ericsson AB); Harald Pobloth (Ericsson AB)
Generating diffusion MRI scalar maps from T1 weighted images using generative adversarial networksXuan Gu (Linköping University)*; Markus Nilsson (Lund University); Hans Knutsson (Department of Biomedical Engineering; Center for Medical Image Science and Visualization (CMIV); Linköping University, Sweden); Anders Eklund (Department of Biomedical Engineering; Department of Computer and Information Science, Linköping University, Sweden)

Prizes

1. Nordic Thesis Award 2017-2018:

Author: Martin Danelljan
Thesis title: Learning Convolution Operators for Visual Tracking

This prize is awarded by the image analysis societies of Denmark, Finland, Norway and Sweden

Nordic Thesis committe 2019:

Anders Nymark Christensen, Denmark
Joni Kämäräinen, Finland
Robert Jenssen, Norway
Per-Erik Forssén, Sweden


2. SCIA 2019 Springer best paper award

Authors: Phong Nguyen-Ha, and Lam Huynh and Esa Rahtu, and Janne Heikkilä
Paper title: Predicting Novel Views Using Generative Adversarial Query Network


3. SCIA 2019 Honourable mention

Authors: Erik Bylow, Robert Maier, Fredrik Kahl, Carl Olsson
Paper title: Combining Depth Fusion and Photometric Stereo for Fine-Detailed 3D Models

The SCIA 2019 award commitee:

Michael Felsberg, Per-Erik Forssén, Ida-Maria Sintorn, Jonas Unger

Submission

The main topics of SCIA 2019 include:

  • 3D vision
  • Color and multispectral image analysis
  • Computational imaging and graphics
  • Faces and gestures
  • Feature extraction and segmentation
  • Biometrics
  • Document analysis
  • Matching, registration and alignment
  • Medical and biomedical image analysis
  • Motion analysis and tracking
  • Object and scene recognition
  • Machine learning and pattern recognition
  • Remote sensing image analysis
  • Robot vision
  • Video and multimedia analysis
  • IR image processing
  • Deep convolutional neural networks
  • Signal processing and applications

Call for papers

Call for papers can be downloaded here.


How to submit a paper to SCIA 2019

The papers can be submitted by following this link. Instructions for the submission will appear in the submission system.

Paper preparation

The maximum allowed length for a paper is 12 pages (single column), including references and appendices (if any). Paper submissions are anonymous, i.e. authors should not write their names and affiliations in the submitted paper.

Papers can be submitted in LaTeX or Word format:

  • LateX2e: we recommend the use of LaTeX2e for the preparation of your camera-ready manuscript, together with the corresponding Springer class file. The ZIP archive with the LaTeX template and relative instructions can be downloaded here.
  • Word: we do not encourage the use of Microsoft Word, particularly as the layout of the pages (the position of figures and paragraphs) can change between printouts. However, we do provide the relevant template. Please read the explanatory typing instructions "SPLNPROC Word 2007-2010 Technical Instructions.pdf" contained in the ZIP archive carefully. The template can be downloaded here.
  • Word 2003: A document template has been prepared by Springer for use with Word 2003. Predefined style formats are available for all the types of content that are part of a computer science proceedings paper, and these formats can be easily accessed via special toolbars. The ZIP archive with the template can be downloaded here.

Camera ready submission

Papers accepted for presentation must be resubmitted by April 3 in the submission system. The resubmission must consists of 3 different files:

  1. the source files (LaTeX or Word) of the revised version of the manuscript. If your manuscript is written in LaTeX, you must ensure to provide all the figures, bibliography and additional manuscript files necessary to compile the final PDF. All the files should be included into a single ZIP file;
  2. a separate file containing the answers to the reviewer comments, explaining how you addressed their critics and suggestions in the revised version of the manuscript;
  3. a signed version (in PDF) of Springer copyright, available for download at the link below.

Copyright submission

Authors whose paper has been accepted for presentation in SCIA 2019 must download and compile the Springer copyright form, necessary for the publication in the Springer proceedings. The copyright form must be compiled as follows:

  • Title of the Book or Conference Name: SCIA 2019.
  • Volume Editor(s): Jonas Unger, Michael Felsberg, Per-Erik Forssén, Ida-Maria Sintorn
  • Title of the Contribution: title of the paper submitted to SCIA 2019.
  • Author(s) Name(s): complete names of all the authors of the paper submitted to SCIA 2019.
  • Corresponding Author's Name, Address, Affiliation and Email: information of the corresponding author of the paper submitted to SCIA 2019.

The copyright form must be signed by the corresponding author of the paper and the three boxes in the end must be checked, only if one of the categories apply. Once the form is filled, it must be scanned and converted ina PDF file, which has to be sent along with the files required for the camera ready version of the manuscipt (see above), before April 3.

The copyright form can be downloaded here.

Oral presentations

Papers scheduled as orals have an allotted 15mins for their talks. Each talk is followed by a 3min Q&A session, where the next author also prepares to speak. Papers selected for oral presentation also have the option to present a poster, see details above. If you choose to also present a poster, make sure to mention this during the talk, as the talk then serves as your spotlight.

Poster presentations

For papers scheduled as posters there are both a poster session and a spotlight. The poster boards are wide enough to accommodate a 1m wide poster. Two common poster sizes that fit are A1 landscape, or A0 portrait. Note that there is no poster printing service at SCIA. Instead we ask you to print your poster beforehand, and bring it to the conference.

Each poster presenter is also offered a poster spotlight presentation before the poster session. A spotlight lasts 3 minutes (with hard cutoff, and no time for questions, save these for the poster session). Use the spotlight to draw interest to your poster, rather than trying to explain all the details. The spotlight presentation (slides in pdf-format, recommended 1 title + 3 slides) must be uploaded latest on June 10 via: https://cmt3.research.microsoft.com/SCIA2019 (opens June 3).

Original research and double submissions

The research papers must neither been published nor submitted for publication elsewhere. Preprints (such as ArXiv) are accepted.

Proceedings

Papers accepted for the SCIA 2019 conference will be published in Lecture Notes in Computer Science Proceedings, Springer. All figures will be in black and white in the printed publication.

Registration

Registration to SCIA 2019 and SSDL is now open. Early bird registration is available until April 7.

Register to SCIA 2019, SSDL or SCIA 2019 + SSDL here.


Registration fees

VenueTypeEarly registration
(deadline April 7)
Regular registrationOn-site registration
SCIA Members 5000SEK6000SEK7000SEK
SCIA Non-members 5500SEK6500SEK7500SEK
SCIA Student members 3600SEK4600SEK5600SEK
SCIA Student non-members 4100SEK5100SEK6100SEK
SSDL + SCIA Members 6250SEK7250SEK8750SEK
SSDL + SCIA Non-members 6750SEK7750SEK9250SEK
SSDL + SCIA Student members 4850SEK5850SEK7350SEK
SSDL + SCIA Student non-members 5350SEK6350SEK7850SEK
SSDL All 1250SEK1250SEK1750SEK

Venue

SCIA 2019 will be held at Norrköping Visualization Center C at Linköping University, Campus Norrköping located in the old industrial landscape close to Norrköping city center:


Norrköpings Visualiseringscenter C
Kungsgatan 54
602 33 Norrköping



Travel

Traveling to Norrköping from outside of Sweden is easy. The closest airport is in the nearby city of Linköping with flights from and to the Schiphol airport in Amsterdam. Linköping airport is accessed to and from Norrköping by taxi or by taking a shuttle or bus to Linköping train station. The local train is operated by Östgötatrafiken leaves from Linköping Resecentrum to Norrköping Resecentrum 3-4 times every hour. Another option is Skavsta airport which operates Ryanair flights from several destinations in Europe and is accessed by frequent airport busses to and from Norrköping. The Arlanda airport in Stockholm can be reached from most major airports and is accessed by several daily direct trains to and from Norrköping.


Social events

The SCIA 2019 conference reception on Tuesday June 11 will be held at the Visualization Center and include a mingle and visits to the public exhibitions and the dome theatre. The conference dinner in the evening on Wednesday June 12 will be held at in Östgöta kök's restaurant at Nya Torget close to Norrköping city center.

Directions to the conference dinner:


Östgöta kök
Hospitalsgatan 30
602 27 Norrköping



Norrköping

Norrköping is located approximately 1.5 hours south of Stockholm. From the 17th century to the middle of the 20th century, it was the place of a number of large industries located along the Motala river that floats through the city. The city was a large producer of textiles, and has often been nicknamed "Sweden's Manchester". Today, the former industries have been restorated and transformed into a unique environment that hosts a number of innovative companies, museums, conference center, the Visualization Center C, as well as the Norrköping Campus of Linköping University.

For more information about Norrköping, see for example the experience Norrköping website.

Important dates


Paper submission opens December 3, 2018
Paper submission deadline January 30  February 6, 2019
Notification of acceptance March 21, 2019
Submission of camera ready manuscript April 3, 2019
Early-bird registration deadline April 7, 2019
Conference June 11-13, 2019

Sponsoring

New for this year is that the sponsorship packages cover both SCIA and SSDL. Our sponsorship packages for SCIA and SSDL offer a unique opportunity to:

  1. Network with the leading research groups in the Nordic countries
  2. Gain visibility before, during, and after the conference
  3. Meet and recruit undergraduate students, graduated or soon to graduate PhD students


Choose one of our sponsorship options:

A. Silver sponsorship, SEK 15,000

  1. Your logo on the conference website
  2. Acknowledgement of your support during the conference

B. Gold sponsorship, SEK 30,000

  1. All Silver sponsorship & Exhibitor benefits
  2. Distribution of short materials (brochure, bag items) that you provide in advance

C. Exhibitor, SEK 15,000

  1. Demonstration & exhibition space for demonstrations and promotional material
  2. One free ticket to the conference included
  3. We kindly ask that all exhibitors appear with a booth in the exhibition area and notify the conference organizers which days you plan to attend

For more information and booking, please contact Daniel Jönsson.

Organization

General Chair

  • Jonas Unger
  • Department of Science and Technology
  • Linköping University
  • jonas.unger@liu.se

Program Chairs

Web Chair

Sponsors Chair


International program committee

NameEmailAffiliation
Adrien Bartoli adrien.bartoli@gmail.com Université Clermont Auvergne, France
Anders Bjorholm Dahl abda@dtu.dk Technical University of Denmark
Anders Heyden anders.heyden@math.lth.se Lund University, Sweden
Atsuto Maki atsuto@kth.se KTH Royal Institute of Technology, Sweden
Carl-Fredrik Westin westin@bwh.harvard.edu Harvard University, United States
Cristina Soguero Ruiz cristina.soguero@urjc.es Rey Juan Carlos University
Domenico Bloisi bloisi@dis.uniroma1.it University of Basilicata, Italy
Einar Heiberg einar.heiberg@med.lu.se Lund University, Sweden
Erkki Oja erkki.oja@hut.fi Aalto University, Finland
Ewert Bengtsson ewert@cb.uu.se Uppsala University, Sweden
Fahad S. Khan fahad.khan@liu.se Inception Institute of Artificial Intelligence, United Arab Emirates
Filip Malmberg filip.malmberg@it.uu.se Uppsala University, Sweden
Francesco Ciompi francesco.ciompi@radboudumc.nlRadboud University Medical Center, Netherlands
Fredrik Kahl fredrik@maths.lth.se Lund University, Sweden
Gunilla Borgefors gunilla.borgefors@it.uu.se Uppsala University, Sweden
Gustau Camps-Valls gcamps@uv.es University of Valencia
Heikki Kälviäinen heikki.kalviainen@lut.fi Lappeenranta University of Technology
Helene Schulerud helene.schulerud@sintef.no SINTEF
Hugues Talbot hugues.talbot@esiee.fr Université Paris Est, France
Ingela Nyström ingela.nystrom@it.uu.se Uppsala University, Sweden
Janne Heikkila janne.heikkila@ee.oulu.fi University of Oulu, Finland
Jens T. Thielemann jens.t.thielemann@sintef.no SINTEF
Joel Kronander joel.kronander@ninesai.com Nines
Joni-Kristian Kamarainen joni.kamarainen@tut.fi Tampere University, Finland
Kalle Åström kalle@maths.lth.se Lund University, Sweden
Kim Pedersen kimstp@di.ku.dk University of Copenhagen, Denmark
Kjersti Engan kjersti.engan@uis.no University of Stavanger
Lasse Østergaard lasse@hst.aau.dk Aalborg University
Lorenzo Livi lorenz.livi@gmail.com University of Manitoba, Canada
Mads Nielsen madsn@di.ku.dk University of Copenhagen, Denmark
Maria Magnusson maria.magnusson@liu.se Linköping University, Sweden
Marius Pedersen marius.pedersen@ntnu.no NTNU, Gjovik, Norway
Natasa Sladoje natasa.sladoje@it.uu.se Uppsala University, Sweden
Robert Jenssen robert.jenssen@uit.no UiT - The Arctic University of Norway
Robin Strand robin.strand@it.uu.se Uppsala University, Sweden
Simone Scardapane simone.scardapane@uniroma1.it Sapienza University
Thomas Moeslund tbm@create.aau.dk Aalborg University
Volker Krueger volker.krueger@cs.lth.se Lund University, Sweden
Walter Kropatsch krw@prip.tuwien.ac.at TU Wien, Austria