Computer Vision ET2428

Course overview

Computer vision as a field is an intellectual frontier and like any frontier, it is exciting. Computer vision uses statistical methods to disentangle data using models constructed with the aid of geometry, physics and learning theory. Thus, it relies on a solid understanding of cameras and of the physical process of image formation to obtain simple inferences from individual pixel values, combine the information available in multiple images into a coherent whole, impose some order on groups of pixels to separate them from each other or infer shape information, and recognize objects using geometric information or probabilistic techniques. Computer vision has a wide variety of applications, old (e.g., mobile robot navigation, industrial inspection, and military intelligence) and new (e.g., human computer interaction, image retrieval in digital libraries, medical image analysis, and the realistic rendering of synthetic scenes in computer graphics).

 

 

For more information view the Computer Vision course homepage

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