Machine vision
R A Jarvis
6 points * 39 hours of lectures and practical work * Irregular availability * Clayton
Objectives The student is expected to acquire knowledge about instruments and computational methodologies which support the functional emulation of biological vision systems in the context of industrial and other applications.
Synopsis Human vision systems including optical illusion, image segmentation, consistent scene labelling, blocks world experiments, range finding methodologies, 3D vision systems, semantic guidance and semantic-free systems; industrial vision systems; active vision, optical flow; free-form shape analysis including pose and recognition; robotic application contexts.
Assessment Examinations: 100%
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