EMVA Previews 6th European Machine Vision Forum

The European Machine Vision Forum is an annual event of the European Machine Vision Association – EMVA. The aim is to foster interaction between the machine vision industry and academic research to learn from each other, discuss the newest research results as well as problems from applications, learn about emerging application fields, and to discuss research cooperation between industry and academic institutes. The overall aim is to accelerate innovation by translating new re­search results faster into practice.

The forum is directed to scientists, development engineers, software and hardware engineers, and programmers both from research and Industry.

What to expect

• Plenary sessions with carefully selected contributed and invited talks, presenting a broad variety of a focused topic of the forum.
• Extended coffee and lunch breaks and evening get-together for Networking.
• Teaser sessions dedicated to poster presentations as well as hardware and software demonstrations with ample room for discussions in small groups. Each participant can submit papers and posters for free and also show demos (table-top exhibition possibilities).

Each participant will receive a certificate of his participation detailing the program.

Researchers and developers from machine vision, computer vision, machine learning, applied optics and photonics meet at the forum to exchange their newest ideas.

Machine vision solutions provide great value to end-users, but also must function well in real-world environments like agriculture, environmental monitoring, industrial and medical applications. Depending on the application at hand, specific challenges arise which concern the variability of the vision task as well as possible disturbances or operational conditions, for example:

• Large varieties of disturbances (e.g., vibrations, motion in the scene, variable illumination, ambient light variations of the background)
• Variations of the objects to be inspected (high inter-class variability, e.g. for fruits), which may lead to insufficient training data for machine learning
• Unknown camera poses (e.g., for moving imaging platforms)

In consequence, real-world machine vision systems must be able to deal with such undesired variability. Several approaches are conceivable to address the issues:

• How can machine vision system (hardware and software) be designed to be independent of unwanted variation and external influences?
• What hardware combinations (including imaging sensors) are robust to a large variety of disturbances or interference?
• What preprocessing and evaluation methods are suitable to deal with such variabilities and disturbances?
• How can machine learning be used and adapted in such cases?
• Can simulations be used to model the physics of real-world scenarios?
• What is the trade-off between robustness and accuracy?
• How can the reliability of machine vision systems be assessed and specified when variabilities and disturbances are present?

You are invited to submit your valuable contribution to this focal topic. Submit your extended abstract for a contributed talk or poster no later than May 16th, 2023, via this Application Form.

All submissions are openly reviewed by the joint Scientific and Industrial Advisory Board of the forum.

Find out more about EMVA.