The research of our group focuses on the investigation of mechanisms and the underlying structure of visual information processing in biological and technical systems (biological and machine vision) as well as their adaptation to changing environments (visual learning).
Our research program utilizes an integrative approach based on the analysis of empirical data derived from psychophysics, neuroscience and imaging studies, and the mathematical and computational investigation of the underlying neural processes. We conduct psychophysical experiments in our computational perception lab utilizing 2D and 3D Computer Graphics methods as well as using eye tracking facilities. The results of neural modeling gain new insights into the computational mechanisms underlying complex brain functions for visual sensory processing and to guide behaviourally relevant tasks. These investigations also steer the development of new approaches and mechanisms for computational vision. Even further, these developments are applied in several domains, such as perceptual and attentive human-computer interfaces, biometric systems, automotive technologies, medical image analysis and recognition, and visually-guided robotics.