Workshop 8

Applied Vision

Applied Vision (AV 2024)

The workshop provides a platform for presentation and discussion of research progress as well as current projects within the OAGM community. We additionally focus on interdisciplinary research of computer vision and pattern analysis in the context of Applied Vision. The aim is to bring together Austrian and nearby located groups, researchers, and students working on interdisciplinary topics for discussion and establishing potential collaborations.

Contributions to the workshop cluster around the following topics:

  • 3D vision, stereo, and structure from X
  • Animal and plant phenotyping
  • Cultural heritage
  • Cyber-physical systems
  • Document analysis
  • Embedded and mobile computer vision / machine learning
  • Explainability, ethics, and fairness in computer vision / machine learning
  • Image denoising, restoration & enhancement
  • Image, video, and multimodal retrieval
  • Industrial assistance systems
  • Inspection and quality assurance
  • Motion and tracking
  • Multi- and hyperspectral image analysis
  • Object/scene detection, recognition, and categorization
  • Pattern analysis (visual and non-visual data)
  • Precision agriculture and precision forestry
  • Remote sensing and earth observation
  • Sensors and information fusion
  • Video analysis and event recognition
  • Vision datasets, benchmarking, and performance evaluation


Invited Talk

Collaborative robotics for sustainable manufacturing - Cobotic Induction System for Garment Picking

Fabio Pini, PhD Researcher On Integrated Design Methodologies For The Development Of Industrial/Collaborative Robotic Solutions; University Of Modena And Reggio Emilia. The growing trend of garments waste highlights the need of effective and affordable processes to enable a more sustainable lifecycle. Collaborative robotic systems that support operators represent a feasible solution, but there are still some limitations related to the manipulation of deformable objects, such as garments. By integrating versatile gripper system and machine learning models trained to detect each garment, this work suggests a solutions to automate garments picking. The first experiments highlight interesting results about effective grasping and promising further improvements about the productivity.

Fabio Pini is a tenure track Professor at the “Enzo Ferrari” Engineering Department at the University of Modena and Reggio Emilia (UNIMORE). He specializes in Design Methods for Industrial Engineering and conducts research in Computer Aided Design for Product Lifecycle Management. He also focuses on designing collaborative and industrial robotics solutions. Additionally, he teaches in various engineering degree programs at UNIMORE.

Contributed talks (12 min + 3min questions)

First Session Wednesday March 27, 2024 9:00-10:30

  • Manuel Krammer, “Camera-based High-Speed Rolling Mark Detection” (ID: 10)
  • Malte P Jaschik, Harald Ganster, Maria Kainz, Maria Jernej, “Initial Results on Hyperspectral Characterization of Steel Scrap” (ID: 48)
  • Florian Kromp, David Brunner, Johannes Zellinger, Alexander Valentinitsch, Ozan Cakiroglu, Clara Schachner, Lukas Fischer, “Robustness of One-Class Visual Anomaly Detection Methods” (ID: 45)
  • Lukas Brunner, Thomas Pönitz, “Simulating Human Perception: Crafting Datasets for Advanced Print Defect Detection on Packaging Foil” (ID: 47)

Second Session Wednesday March 27, 2024 11:00-12:30

  • Viktoria Pundy, Marco Peer, Florian Kleber, “Transparency Techniques for Neural Networks trained on Writer Identification and Writer Verification” (ID: 25)
  • Werner Ainhauser, Martin Welk, “Parameter Identification for Pattern-Generating Reaction-Diffusion Systems – Towards Generative Texture Descriptors” (ID: 17)
  • Sead Mustafic, Dominik Dachs, Rainer Prüller, Florian Schöggl, Roland Perko, “Supporting Image-Based Wildlife Classification” (ID: 1)
  • Javier Ureña Santiago, Antonio J Rodriguez-Sanchez, “Solving Microorganism Enumeration through Weakly-Supervised Counting with Vision Transformers - A comparative study” (ID: 27)
  • Tingyu Lin, Robert Sablatnig, “Enhancing Historical Image Retrieval with Compositional Cues” (ID: 43)
  • Katharina Hofer-Schmitz, Sead Mustafic, Karlheinz Gutjahr, Roland Perko, “Advanced Despeckling Based on Real SAR Intensity Images” (ID: 6)

Program and Time Table

Program and Time Table


  • DI Dr. Harald Ganster (Joanneum Research)
  • DI Dr. Florian Kleber (Vienna University of Technology)
  • Priv.-Doz. DI DI Dr. Roland Perko (Joanneum Research)
  • DI Dr. Gernot Stübl (Profactor GmbH)
  • DI Dr. Martina Uray (Joanneum Research)

Program Committee

  • Doris Antensteiner - Austrian Institute of Technology
  • Christof Bertram - University of Veterinary Medicine
  • Csaba Beleznai - Austrian Institute of Technology, Austria
  • Harald Ganster - Joanneum Research
  • Katharina Hofer-Schmitz - Joanneum Research
  • Florian Kleber - Vienna University of Technology
  • Martin Kampel - Vienna University of Technology, Computer Vision Lab
  • Olaf Kaehler - Joanneum Research
  • Christoph Lampert - IST Austria
  • Christoph Praschl - University of Applied Sciences Upper Austria
  • Roland Perko - Joanneum Research
  • Robert Sablatnig - Vienna University of Technology
  • Josef Scharinger - Johannes Kepler University Linz
  • Gernot Stübl - Profactor GmbH
  • Stefan Thumfart - RISC Software GmbH
  • Martina Uray - Joanneum Research
  • Martin Welk - UMIT TIROL
  • Peter M. Roth - University of Veterinary Medicine, Vienna
  • Matthias Zeppelzauer - St. Pölten University of Applied Sciences
  • Gerald Zwettler - University of Applied Sciences Upper Austria