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要旨:
In our Perceptual Graphics group at the Max Planck Institute for Biological Cybernetics we integrate methods from psychophysics, computer graphics and computer vision in order to understand fundamental perceptual and cognitive processes. The fusion of methods from these research areas has the potential to greatly advance our understanding of perception and cognition. Highly controllable, yet realistic computergenerated stimuli offer novel ways for psychophysical investigations. The results from those experiments can in turn be used to derive perceptual "shortcuts" to more efficient rendering approaches. Computer vision and machine learning algorithms can be used to model human cognition and action while conversely, the results from perceptual experiments can inform computer scientists how the brain solves problems and thus can lead to more efficient solutions of hard problems like recognition and categorization. In this presentation, I will highlight how the latest tools in computer vision, computer graphics, and virtual reality technology can be used to systematically understand the factors that determine how humans behave and solve tasks in realistic scenarios.
