Computer Vision

Computer vision designs algorithms that infer properties of the world from the outputs of a variety of imaging sensors. Application examples include the analysis of medical images for diagnostic purposes, the recognition of people from their faces, retinas, or fingerprints for authentication, the reconstruction of the three-dimensional shape of objects and scenes from multiple images for autonomous driving or architectural surveys, the recognition of objects for robotics applications or for assistance to the visually impaired, the analysis of biological microscopy images or video for measuring cell growth or for categorizing plant species from the shapes of their leaves, and much more. Computer vision research at Duke enables applications like these by developing foundational concepts and algorithms for video analysis, object and activity recognition, and shape reconstruction, and by collaborating with interdisciplinary teams to develop applications. More information is available: Duke Robotics Intelligence and Vision.