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Computer Vision

Computer vision is the science and technology of machines that see. As a scientific discipline, computer vision is concerned with the theory behind artificial systems that extract information from images. The image data can take many forms, such as video sequences, views from multiple cameras, or multi-dimensional data from a medical scanner.

As a technological discipline, computer vision seeks to apply its theories and models to the construction of computer vision systems.

Computer vision is, in some ways, the inverse of computer graphics. While computer graphics produces image data from 3D models, computer vision often produces 3D models from image data. There is also a trend towards a combination of the two disciplines.

An intelligent computer system can go a long way in reducing human labor. However, if such a system can be provided with a method of actually interacting with the physical world, its usefulness is greatly increased. Robotics gives AI the means to exhibit real-world intelligence by directly manipulating their environment. That is, robotics gives the artificial mind a body.

An essential component of robotics has to do with artificial sensory systems in general and artificial vision in particular. While it is true that robotics systems exist (including many successful industrial robots) that have no sensory equipment (or very limited sensors) they tend to be very brittle systems. They need to have their work area perfectly lit, with no shadows or mess. They must have the parts needed in precisely the right position and orientation, and if they are moved to a new location, they may require hours of recalibration. If a system could be developed that could make sense out of a visual scene it would greatly enhance the potential for robotics applications. It is therefore not surprising that the study of artificial vision and robotics go hand-in-hand.

  1. September 7th, 2010 at 18:29 | #1

    Thank you for information.

  2. Maverick’s Review
    September 15th, 2010 at 22:25 | #2

    Found this on Google, great post.

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