Computer vision
Computer vision is a subfield of artificial intelligence. The purpose of computer vision is to program a computer to "understand" a scene or features in an image.
Typical goals of computer vision include:
- The detection, segmentation, localisation, and recognition of certain objects in images (e.g., human faces)
- The evaluation of results (e.g., segmentation, registration)
- Registration of different views of the same scene or object
- Tracking an object through an image sequence
- Mapping a scene to a three-dimensional model of the scene; such a model might be used by a robot to navigate the imaged scene
- Estimation of the three-dimensional pose of humans and their limbs
- Searching for digital images by their content (content-based image retrieval)
These goals are achieved by means of pattern recognition, statistical learning, projective geometry, image processing, graph theory and other fields. Cognitive computer vision is strongly related to cognitive psychology and biological computation.
In the related fields machine vision and medical imaging, systems using computer vision techniques are sold in markets worth billions of US dollars per year.
One interesting application of computer vision, commonly used in the creation of visual effects for cinema and broadcast, is camera tracking or matchmoving. Computer vision also finds its applications in medicine, military industry, security and surveillance, quality inspection, robotics, automotive industry and many other fields.
See also
- artificial intelligence
- image processing, digital image processing
- machine vision
- medical imaging
- morphological image processing
- Herbert Freeman
- David Marr
- Jerome H. Lemelson
- Affective computing
- Computer graphics
- Important publications in computer vision
External links
- The Computer Vision Homepage
- On-Line Compendium of Computer Vision
- Keith Price's Annotated Computer Vision Bibliography
- Xiris: Developer of custom machine vision automation systems and software.
- Computer vision wikicity
- Tutorial to Image Processing
- introduction to computer vision