Talk by Michael Herzog, École Polytechnique Fédérale de Lausanne, on “Crowding, Masking, and the Fundamentals of Vision”
Time: 10-11 am
Location: Liebermeisterstraße 18 (ZITh), R. 318, and via research colloquium zoom.
Abstract: Vision is usually explained by (feedforward) models, where visual features are analyzed in a hierarchical fashion starting with simple, but fine-grained, feature analysis (V1). Higher visual areas pool information from lower ones to detect increasingly complex features, losing information in the process. Results of psychophysical studies are typically explained within this framework, and convolutional networks are thought to be good models of this processing. For example, in crowding, human perception of a target is hindered by nearby elements because, as proposed, responses of neurons coding for nearby elements are pooled. A clear-cut prediction is that adding additional elements can only further impair performance. However, as I will show, this prediction is strongly and systematically countered by many psychophysical and neuroimaging experiments. It seems we need to rethink the fundamentals of the standard models of vision. I will show that the basic assumption of the existence of ordinary objects is not met and, hence, subsequent arguments are based on sand.
