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Vision systems developed to date do not have the ability of humans in terms of
understanding complex indoor or outdoor scenes. Successful machine vision
systems need to have a highly constrained environment.
Why is vision hard?
- The world is three-dimensional. Images formed in a camera are
two-dimensional projections -- some information has been lost and is difficult
to recover.
- The image is dependent on many factors:
- The nature of the sensing device -- vidicon, CCD, infra-red, greyscale,
colour.
- Properties of the device -- sensitivity, resolution, lenses, stability,
focus.
- The lighting of the scene -- poor lighting gives poor contrast, shadows
or excessive reflections may also give problems.
- The environment -- dust, fog, humidity.
- The reflective properties of the object surfaces -- texture, colour,
specularity.
- A large volume of information has to processed. Whilst this is good in
general many vision algorithms require high performance computations.
- Much knowledge about the world - both objects and environment - might
need to be represented for vision algorithms.
What sort of operations does a vision system need to perform and why is this
relevant to AI?
- Describe images, objects and physical world -- clearly we need
(mathematical) models of the image and object and need some knowledge
representation scheme as well.
- Image processing -- improve images for human or computer consumption.
Highlight/extract relevant features.
- Segmentation -- extract features such as edge, regions, surfaces and other
descriptions from an image.
- Pattern recognition -- for single object images, classify the image.
- Measurement analysis -- measure features on the object.
- Image understanding - for multiple object images locate objects in the
image, classify them and perhaps build three-dimensional model of the scene.
The Ultimate aim of a vision system is to recognise objects with in an
image.
Clearly many AI techniques -- knowledge representation, reasoning,
understanding, planning and learning -- are required in the visual
process
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dave@cs.cf.ac.uk