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CV for Per-Erik Forssén

Academic Degrees

Academic Degrees

  • October 2009: Docent in Computer Vision
    Talk title: "Robot Vision, More than Meets the Eye"
  • March 2004: Doctor of Philosophy in Computer Vision
    PhD thesis: "Channel Representations for Low and Medium Level Vision", Supervisor Prof. Gösta Granlund.
  • February 2001: Licentiate of Engineering in Computer Vision
    Licentiate thesis (halftime PhD): "Sparse Representations for Medium Level Vision", Supervisor Prof. Gösta Granlund.
  • December 1997: Master of Science in Computer Science and Engineering
    Master's Thesis: "Detection of Man-made Objects in Satellite Images", Work conducted at the Swedish Space Corporation in Kiruna, Sweden. Supervisor Dr. Sören Molander.

Employment History

Employment History

  • February 2020 - present
    Associate Professor (Biträdande professor), Linköping University
  • January 2013 - January 2020
    Associate Professor (Universitetslektor), Linköping University
  • April 2009 - December 2012
    Assistant Professor (LiU Foass), Linköping University
  • May 2008 - March 2009
    Research Associate, Linköping University
  • January 2008 - April 2008
    Research Engineer, Computer Vision Lab, Linköping
  • January 2006 - December 2007
    Post-doctoral Fellow, University of British Columbia, Canada
  • June 2004 - December 2005
    1st Research Engineer, 20% teaching, Computer Vision Lab, Linköping
  • May 2004 - December 2005
    Computer Vision Consultant, (15-25 h/month) ATS AB, Linköping
  • November 1998 - May 2004
    PhD Student Position (20% teaching), Computer Vision Lab, Linköping
  • July 1998 - November 1998
    Teaching Assistant/Programmer, Computer Vision Lab, Linköping
  • Spring 1998
    English Language Studies (Full Time), Linköping University
  • Summer 1996
    Assistant Computer Network Analyst, SEMA Group, Örebro and Stockholm
  • June 1994 - August 1995
    Military Service, Technician/Under-Officer
  • August 1992 - December 1997
    Studies in Computer Science and Engineering Programme (with breaks for military service and summer employment)

Awards and memberships

Awards and memberships

Publications

Teaching

Teaching

  • TSBB19 Machine Learning for Computer Vision, LiU, Examiner and lecturer, Autumn 2021.
  • WASP Project course, WASP, Project supervisor. Autumn 2019, Autumn 2021 (2 groups).
  • WASP Learning feature representations, WASP, Lecturer. Autumn 2020.
  • AI och Digitalisering, Översiktskurs, LiU, Course development, lectures and a computer lab in an external course managed by LiU Uppdagsutbildning.
  • TSBB06 Multidimensional Signal Analysis, LiU, Acting examiner and lecturer Autumn 2018.
  • TSBB17 Visual Recognition and Detection, LiU, Examiner and lecturer, Autumn 2018, Autumn 2019, Autumn 2020.
  • Visual Object Recognition, 8hp. LiU Course development of a graduate course. Updated course content, gave 8 lectures, and selected articles for reading. Attended by 15 PhD students, and 15 external people. Autumn 2014 and Spring 2015
  • Geometry for Computer Vision, 6hp. with Klas Nordberg. Updated course content and gave 5 of the lectures. Spring 2014
  • Biological Vision Systems, 6hp. LiU Course development of a graduate course together with Michael Felsberg. The course featured 4h lectures and 32h of student led seminars. It had 16 attendees (11 presenting PhD students, 5 other participants). Selected all papers and topics and moderated the seminars. Spring 2013
  • Computer Vision, LiU Course development of an external course held at Saab Dynamics with Michael Felsberg. Extent: 5 lectures totalling at 10h. Spring 2013
  • Computer Vision on Rolling Shutter Cameras. Tutorial held at the CVPR 2012 conference. (with Erik Ringaby and Johan Hedborg)
  • TSBB15 Computer Vision, LiU, Examiner and course manager, Teaching 6h+6h preparations, Spring 2012, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, Spring 2018, Spring 2019, Spring 2020, Spring 2021.
  • TNM089 Imaging Technology, LiU, Guest Lecturer, 2h+4h preparations, Autumn 2011
  • Geometry for Computer Vision, LiU Course development of a graduate course together with Klas Nordberg. extent: 8hp. The course featured 16h lectures, 23 attendees (9 PhD students, 14 from industry), written exam for 6 people, corrected and supervised project assignments. Spring 2010
  • TS1017 Computer Vision, LiU, Teaching 4h+4h, Spring 2011
  • TSBB12 Computer Vision, LiU, Teaching 8h+8h preparations, Contributed to course development, Spring 2009, Teaching 8h+8h Spring 2010
  • Visual Object Recognition, LiU, Complete course development of a graduate course, extent:8hp, teaching 14h lectures, 24 attendees (11 PhD students, and 13 from local companies), Written exam for 11 people, corrected and supervised project assignments, Autumn 2008
  • TSBB09 Image Sensors, LiU, Contributed to course development in a new undergraduate course, Assisted students during one 4h computer session, Autumn 2008, Demo of Kinect Autumn 2010, Demo and talk on Kinect Autumn 2011.
  • CVL Article Club, LiU, Planning and execution of a seminar series covering the latest research in Computer and Robot Vision, also offered as a PhD course, Spring 2008, Spring 2009 - ongoing.
  • 525 Image Understanding II, UBC, guest lecturer. Spring 2006
  • TSBB04 Computer Vision, LiU, assistant lecturer, lab-exercise development. Autumn 1999, Autumn 2000, Autumn 2001, Autumn 2002, Autumn 2003, Autumn 2004, Autumn 2005
  • TSBB35 Multidimensional Signal Analysis, LiU, project supervisior, lab-exercise development. Autumn 2000, Spring 2001, Spring 2002, Spring 2003, Spring 2004, Spring 2005
  • TSBB65 Images and Graphics, LiU, computer excersise assistant. Spring 2001, Spring 2002, Spring 2003, Spring 2004, Spring 2005
  • TSBB53 Images and Graphics, Project Course, LiU, project development and supervision. Spring 2003, Spring 2004, Spring 2005

Supervised and Examined Masters

Supervised and Examined Masters

  • Supervised Robert Söderberg
    View Dependent Recognition of Objects, February 2002
  • Supervised Andreas Böckert
    Vehicle Detection and Classification in Video Sequences, August 2002
  • Supervised Per Öberg
    Tracking By Image Processing in a Real-Time System, March 2003
  • Examined Jan-Willhelm Isoz
    Calibration of Multispectral Sensors, December 2005
  • Examined Markus Olgemar
    Camera Based Navigation, October 2008
  • Examined Marcus Wallenberg
    A Single-Camera Gaze Tracker using Controlled Infrared Illumination, March 2009
  • Examined Alexander Tuttle
    Saliency Maps using Channel Representations, January 2010
  • Examined Anders Lind
    High-speed View Matching using Region Descriptors, August 2010
  • Examined Axel Landgren
    A Robotic Camera Platform for Evaluation of Biomimetic Gaze Stabilization using Adaptive Cerebellar Feedback, September 2010
  • Examined Andreas Schöndell
    Evaluation of methods for segmentation of 3D range image data, January 2011
  • Examined David Sandberg
    Model-Based Video Coding Using a Colour and Depth Camera, June 2011
  • Examined Gustav Hanning
    Video Stabilization and Rolling Shutter Correction using Inertial Measurement Sensors, June 2011
  • Examined Tobias Lundqvist
    3D mapping with iPhone, October 2011
  • Examined Anton Nordmark
    Kinect 3D Mapping, October 2012
  • Examined Magnus Stigson
    Object Tracking Using Tracking-Learning-Detection in Thermal Infrared Video, May 2013
  • Examined Victor Johansson
    3D Position Estimation of a Person of Interest in Multiple Video Sequences: Person of Interest Recognition, September 2013
  • Examined Johannes Markström
    3D Position Estimation of a Person of Interest in Multiple Video Sequences: People Detection, September 2013
  • Examined Eric Gratorp
    Evaluation of online hardware video stabilization on a moving platform, October 2013
  • Examined Morgan Bengtsson
    Indoor 3D Mapping using Kinect, April 2014
  • Examined Felix Järemo Lawin
    Depth data processing and 3D reconstruction using the Kinect v2, August 2015
  • Examined Peter Thulin
    Anomaly detection for product inspection and surveillance applications, September 2015
  • Examined Mikael Jonsson
    Make it Flat: Detection and Correction of Planar Regions in Triangle Meshes, March 2016
  • Examined David Habrman
    Face Recognition with Preprocessing and Neural Networks, May 2016
  • Examined Pontus Lindberg
    Automatic Measurement of Volume for on-Truck Timber Stacks, June 2016
  • Examined Richard Bondemark
    Improving SLAM on a TOF Camera by Exploiting Planar Surfaces, August 2016
  • Examined Ola Grankvist
    Recognition and Registration of 3D Models in Depth Sensor Data, September 2016
  • Examined Lukas Tallund
    Handling of Rolling Shutter Effects in Monocular Semi-Dense SLAM Algorithms, December 2016
  • Examined Alexander Poole
    Real-Time Image Segmentation for Augmented Reality by Combining multi-Channel Thresholds, September 2017
  • Examined Emil Rundgren
    Automatic Volume Estimation of Timber from Multi-View Stereo 3D Reconstruction, October 2017
  • Examined Robert Norlander
    Make it Complete: Surface Reconstruction Aided by Geometric Primitives, October 2017
  • Examined Fredrik Fridborn
    Reading Barcodes with Neural Networks, November 2017
  • Examined Johan Lind
    Make it Meaningful: Semantic Segmentation of Three-Dimensional Urban Scene Models, December 2017
  • Examined Mattias Carlsson
    Neural Networks for Semantic Segmentation in the Food Packaging Industry, February 2018
  • Examined Björn Kernell
    Improving Photogrammetry Using Semantic Segmentation, May 2018
  • Examined Fredrik Olsson
    Feature Based Learning for Point Cloud Labeling and Grasp Point Detection, August 2018
  • Examined Adam Nyberg
    Transforming Thermal Images to Visible Spectrum Images Using Deep Learning, August 2018
  • Examined Victor Tranell
    Semantic Segmentation of Oblique Views in a 3D Environment, January 2019
  • Examined Viktor Ringdahl
    Stereo camera pose estimation to enable loop detection, January 2019
  • Examined Jonathan Sjölund
    Detection of Frozen Video Subtitles using Machine Learning, June 2019
  • Examined Carl Ekman
    Traffic Sign Classification using Computationally Efficient Convolutional Neural Networks, June 2019
  • Examined Angelina Johansson and Jacob Grönlund
    Defect Detection and OCR on Steel, June 2019
  • Examined Malcolm Vigren and Linus Eriksson
    End-to-end Road Lane Detection and Estimation using Deep Learning, June 2019
  • Examined Denise Härnström
    Classification of Clothing Attributes Across Domains, February 2020
  • Examined Johan Thornström
    Domain Adaptation of Unreal Images for Image Classification, February 2020
  • Examined Karin Fritz
    Instance Segmentation of Buildings in Satellite Imagery, March 2020
  • Examined Björn Runow
    Deep Learning for Point Detection in Images, June 2020
  • Examined Sabina Serra
    Deep Learning for Semantic Segmentation of 3D Point Clouds from an Airborne LiDAR, August 2020
  • Examined Emir Alkazhami
    Facial Identity Embeddings for Deepfake Detection in Videos, October 2020
  • Examined Mimmi Lindberg
    Forensic Validation of 3D Models, November 2020
  • Examined Erik Örjehag
    Unsupervised Learning for Structure from Motion, March 2021
  • Examined Kerstin Söderqvist
    Anomaly Detection in Images and Videos Using Photo-Response Non-Uniformity, April 2021
  • Examined Lovisa Nilsson
    Data-driven Methods for Sonar Imaging, June 2021
  • Examined Tim Yngesjö
    3D Reconstruction from Satellite Imagery Using Deep Learning, June 2021
  • Examined Marcus Bejgrowicz and Jonas Rydgård
    Semantic Segmentation of Building Materials in Real World Images Using 3D Information, June 2021
  • Examined Gustav Wahlquist
    Improving Automatic Image Annotation using Metadata, June 2021
  • Examined Marcus Dahlqvist
    Adaptive Losses for Camera Pose Supervision, June 2021
  • Examined Malin Rudin
    Evaluation of Optical Flow for Estimation of Liquid Glass Flow Velocity, August 2021
  • Examined Anton Hjert
    Machine Learning for LiDAR-SLAM - In Forest Terrains, November 2021
  • Examined Axel Ahlqvist
    Examining Difficulties in Weed Detection, May 2022
  • Examined Emily Fredriksson
    Classification of Terrain Roughness from Nationwide Data Sources Using Deep Learning, June 2022
  • Examined Justus Karlsson
    GPS-Free UAV Geo-Localization Using a Reference 3D Database, June 2022
  • Examined Emily Olsson
    Lens Distortion Correction Without Camera Access, June 2022
  • Examined Lovisa Stålebrink
    Object Detection via Contextual Information, June 2022
  • Examined Gustav Dahmén and Erica Strand
    Forest Growth and Volume Estimation using Machine Learning, June 2022
  • Examined Paul Bäcker (LiU/ISY - HKA Karlsruhe)
    Stereoscopic Multispectral Photometric Stereo for Road Surface Estimation, August 2022
  • Examined Arvid Karlhede
    Online Camera-IMU Calibration, September 2022
  • Examined Evelina Hult
    Toward Equine Gait Analysis: Semantic Segmentation and 3D Reconstruction, January 2023
  • Examined Matheus Vieira Bernat
    Topical Classification of Images in Wikipedia, January 2023
  • Examined Lovisa Byman and Johanna Carlson
    Generation of Synthetic Traffic Sign Images Using Diffusion Models, May 2023
  • Examined Simon Hermansson
    Learning Embeddings for Fashion Images, June 2023
  • Examined Moltas Enåkander
    ISAR Imaging Enhancement Without High-Resolution Ground Truth, June 2023
  • Examined Erik Lidman
    Visual Bird's-Eye View Object Detection for Autonomous Driving, June 2023
  • Examined Benjamin Bolgakov and Anton Frank (bachelor thesis)
    Camera Calibration for Zone Positioning and 2D-SLAM: Autonomous Warehouse Solutions for Toyota Material Handling, June 2023
  • Examined Ludvig Dillén
    Feature-Aware Point Transformer for Point Cloud Alignment Classification, October 2023
  • Examined William Torberntsson
    Event-based Visual Odometry using Asynchronous Corner Feature Detection and Tracking, May 2024
  • Examined Tai Ta
    Asynchronous Event-Feature Detection and Tracking for SLAM Initialization, May 2024
  • Examined Anton Eldeborg Lundin and Rasmus Winzell
    Low-Power UAV Detection Using Spiking Neural Networks and Event Cameras, May 2024
  • Examined Adam Borgstrand
    Confidence Calibrated Point Cloud Segmentation with Limited Data, June 2024
  • Examined Oskar Savinainen
    Uncertainty Estimation and Confidence Calibration in YOLO5Face, June 2024

Supervision of PhD students

Supervision of PhD students

  • Currently supervising: Ziliang Xiong, Bao Long Tran.
  • Supervised Erik Ringaby (PhD September 2014), Marcus Wallenberg (PhD January 2017), Hannes Ovrén (PhD September 2018), Jens Ogniewski (Lic December 2020), Felix Järemo Lawin (PhD August 2021), Mikael Persson (PhD March 2022)
  • Co-supervised Fredrik Viksten with Prof Forchheimer (PhD September 2010), Fredrik Larsson with Prof Felsberg (PhD November 2011), Johan Hedborg with Prof Felsberg (PhD May 2012), Kristoffer Öfjäll with Prof Felsberg (PhD April 2016), and Bertil Grelsson with Prof Felsberg (April 2019), Gustav Häger with Prof Felsberg (PhD May 2021), and Andreas Robinson with Prof Felsberg (PhD June 2021), Emil Brissman with Prof Felsberg (PhD April 2023).
  • Currently co-supervising: Arvi Jonnarth (Defense Oct 11, 2024).

Committee work

Committee work

  • Member of PhD grading committee (betygskommitté) for Felix Rydell, KTH, June 2024.
  • Licentiate thesis examiner for Johan Jönemo, LiU, March 2024.
  • Member of PhD grading committee (betygskommitté) for Lucas Brynte, CTH, February 2024.
  • Member of PhD grading committee (betygskommitté) for Marcus Klasson, KTH, November 2022.
  • Member of PhD grading committee (betygskommitté) for David Nilsson, LTH, June 2022.
  • Licentiate thesis examiner for Amanda Olmin, LiU, May 2022.
  • Faculty Opponent for Dinh-Cuong Hoang, OrU, December 2021.
  • Member of PhD grading committee (betygskommitté) for Zhongguo Li, LTH, May 2021.
  • Licentiate thesis examiner (betygsförrättare) for Andreas Bergström, LiU, Feb 2020.
  • Member of PhD grading committee (betygskommitté) for Erik Bylow, LTH, April 2018.
  • Member of PhD grading committee (betygskommitté) for Daniel Canelhas, OrU, October 2017.
  • Member of PhD grading committee (betygskommitté) for Mårten Wadenbäck, LTH, April 2017.
  • Member of PhD grading committee (betygskommitté) for Silvio Giancola, Politecnico di Milano, February 2017.
  • Member of PhD grading committee (betygskommitté) for Johan Fredriksson, LTH, December 2016.
  • Member of PhD grading committee (betygskommitté) for Joel Kronander, LiU, December 2015.
  • Member of PhD grading committee (betygskommitté) for Erik Ask, LTH, October 2014.
  • External licentiate thesis reviewer (opponent) for Mårten Wadenbäck, LTH, September 2014.
  • Member of PhD grading committee (betygskommitté) for Daniel Forsberg, LiU, May 2013.
  • Member of PhD grading committee (betygskommitté) for Babak Rasolzadeh, KTH, January 2012.
  • Member of PhD grading committee (betygskommitté) for Jeroen Hol, LiU, June 2011.
  • Member of PhD grading committee (betygskommitté) for Olof Enqvist, LTH, April 2011.
  • Member of PhD grading committee (betygskommitté) for Martin Byröd, LTH, June 2010.
  • External licentiate thesis reviewer (opponent) for Olof Enqvist, LTH, June 2009.
  • Member of PhD grading committee (betygskommitté) for Henrik Andreasson, OrU, September 2008.

Popular Science Presentations

Popular Science Presentations

  • Popular Science Talk: Populärvetenskapliga veckan, 3D-seende hos självkörande bilar och människor, October 27, 2022
  • Intervju: Ny Teknik, Därför ska alla nya mobiler ha en 3d-kamera, August 14, 2019
  • Talk for high-school teachers: 3D-kameror för självkörande bilar och automation. October 4, 2018.
  • Two talks for high-school teachers: Hur fungerar en mobiltelefonkamera? Från bildsensor till beräkningsfotografi och Beräkningsfotografi. October 1, 2015.
  • Invited talk: Varför blir filmklipp från mobiltelefoner ofta så fladdriga?, 2x25 min popular science talks for 120 prospective university students. October 24, 2012.
  • Invited talk at the LiU University board: Att bygga ett synsinne för robotar, September 13, 2011
  • Interview: Östgöta Correspondenten, Slutet för skakiga mobilklipp, August 8, 2011.
  • Robot demo: Robotseende, Quintek-dagarna, March 30, 2011.
  • Invited talk: Seende robotar, hur och varför?, Teknikfestivalen Norrköping, December 1, 2010.
  • Interview: SVT Östnytt, Roboten Eddie kan både se och känna igen, May 10, 2010.
  • Interview: Linköpings Extra, Eddie - en pratglad ettåring, March 29, 2010.
  • Invited popular science talk: How to build a robot that can recognize objects,
    IT workshop at University College Skövde, March 23, 2010
  • Two demonstrations at the annual LiU popular science day, October 14, 2009:
    Gaze-tracker with 3D display, and Robot with object recognition capabilities.
  • Interview: Östgöta Correspondenten, Eddie känner igen sin Teddy, October 7, 2009
  • Interview: TV4 Norrköping, Dator ska varna bilförare för trafikfaror, March 31, 2008
  • Interview: Vetenskapsradion Tekno Radio Show, SR P1, March 26, 2008
  • Interview: BBC Radio Show: Robots and Artificial Intelligence, Sep 23, 2007
  • Interview: New Scientist, I Google, therefore I am, Aug 18, 2007