PeerJ Award Winner: 43rd European Conference on Visual Perception

PeerJ were delighted to sponsor an award for Best Poster at ECVP 2021, and we recently talked to the winner about the research they presented. If you are organising a conference and would like to offer a PeerJ Award, please email communities@peerj.com

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The European Conference on Visual Perception (ECVP) is a travelling conference that is organizied each year at a different location. ECVP features original research on all aspects of visual perception, regardless of the scientific discipline (e.g., vision science, psychology, neuroscience, biology, computer vision), and addresses fundamental questions as well as applications. Due to the situation caused by the COVID-19 pandemic, the 43rd European Conference on Visual Perception, held between the 22nd and the 27th of August 2021, was conducted entirely online. With over 1850 registrations from over 60 countries, the conference was a great success. Moreover, all can continue to watch recorded sessions and poster presentations either through the ecvp2021.org website, or via the related OSF Meetings pages!

Cristina de la Malla, organiser.

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Lynn Schmittwilken

PhD Candidate at Science of Intelligence at the Technical University Berlin.

SCIoI/Felix Noak

Can you tell us a bit about yourself and your research interests?

I am a doctoral researcher in the Computational Psychology lab of Prof. Dr. Marianne Maertens at the Technical University Berlin. Before I joined the cluster Science of Intelligence for my PhD, I studied Psychology and (Computational) Neurosciences at the University of Bremen. As such, I am broadly interested in how the human brain processes information and how we can understand the underlying mechanisms with the help of computational modelling. In my graduate work, I am interested in whether we can account better for human vision if we regard the visual system as being actively involved in processing visual information. Hence, I am currently investigating whether our visual system could use tiny eye jitters to encode basic visual information more efficiently.

What first interested you in this field of research?

I have always been fascinated by how our brain processes complex information and enables us to efficiently interact with the world. To do this, processing visual information is crucial for most humans and other mammals. However, many aspects of visual processing still puzzle us vision researchers. Consistent with the idea that our eyes work like small cameras, we often treat the visual system as a one-way-street which passively receives information through our eyes. However, evidence in the field of active perception shows that vision relies on sensorimotor strategies (including head and eye movements) to extract relevant information. In the same spirit, I think that we should focus more on understanding the strategies that our visual system uses to interact with the environment, if we want to fully understand visual processing. Eventually, I hope that I can contribute to a better understanding of visual processing with my work.

You won the Best Early Career Researcher Poster award at the ECVP2021, can you briefly explain the research you presented?

During ECVP2021, I presented work on a biologically-inspired model of an early visual process in which microscopic eye jitters are used to extract information about object boundaries (or “edges”). For this, I showed some theoretical evidence that robust edge signals naturally emerge in the model as soon as we consider these microscopic eye jitters.

See Lynn’s video tour of the poster here (via Open Science Framework).

What are your next steps? How will you continue to build on this research?

So far, the work that I presented during ECVP2021 is purely theoretical. In the upcoming steps, I want to collect experimental data to further test my model.