Biological Computer Vision explores how principles of biological vision can inspire new approaches to computer vision and artificial intelligence. Bridging visual neuroscience, computational geometry, and machine learning, the course examines binocular stereopsis, foveated sensing, eye movements, visual attention, and active perception, with particular emphasis on the reconstruction and understanding of 3D scenes through purposeful visual exploration.
The course also presents an AI Odyssey, exploring how artificial intelligence can become a partner in scientific research, from conceptual development to computational experimentation. Combining theoretical foundations, biologically inspired architectures, simulations, and experimental prototypes, it investigates new paradigms for active 3D vision while reflecting on the opportunities and challenges of human–AI collaboration in scientific discovery.
(by ChatGPT, OpenAI)
Summary (by Claude Chat, Anthropic)