Computer vision

Computer vision is a field of computer science and mathematics. Computer science takcles the problem of understanding images. That is the field that includes methods for acquiring, processing, analyzing, and understanding images and, in general, high-dimensional data from the real world in order to produce numerical or symbolic information. 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. A theme in the development of this field has been to duplicate the abilities of human vision by electronically perceiving and understanding an image. Understanding in this context means the transformation of visual images (the input of retina) into descriptions of world that can interface with other thought processes and elicit appropriate action. This image understanding can be seen as the disentangling of symbolic information from image data using models constructed with the aid of geometry, physics, statistics, and learning theory.

Sub-domains of computer vision include:

• Scene reconstruction
• Event detection
• Video tracking
• Object recognition
• Object pose estimation
• Motion estimation
• Image restoration

The direct applications of computer vision includes:

• Controlling processes, e.g., an industrial robot.
• Navigation, e.g., by an autonomous vehicle or mobile robot.
• Detecting events, e.g., for visual surveillance or people counting.
• Organizing information, e.g., for indexing databases of images and image sequences.
• Modeling objects or environments, e.g., medical image analysis or topographical modeling.
• Interaction, e.g., as the input to a device for computer-human interaction.
• Automatic inspection, e.g., in manufacturing applications.

See also

Computational intelligence, Mathematical optimization, Computer vision, Artificial Intelligence, Data Analysis, Machine Learning

Material

• http://opencv.org/
• http://opencv-python-tutroals.readthedocs.io/en/latest/

Books

• Forsyth, David A.; Ponce, Jean (2003). Computer Vision, A Modern Approach. Prentice Hall
• Szeliski, Richard (2010). Computer Vision: Algorithms and Applications. Springer-Verlag.
• Linda G. Shapiro; George C. Stockman (2001). Computer Vision. Prentice Hall.
• Tim Morris (2004). Computer Vision and Image Processing. Palgrave Macmillan.
• Reinhard Klette (2014). Concise Computer Vision. Springer
• Prince, Simon J.D. (2012). Computer Vision: Models, Learning, and Inference. Cambridge University Press
• Solem, Jan Erik (2012) Programming Computer Vision with Python: Tools and algorithms for analyzing images. 2nd Edition, O’Reilly Media
• Hartley, Richard; Zisserman, Andrew (2004). Multiple View Geometry in Computer Vision. Cambridge University Press
• Bradski, Gary; Kaehler, Adrian (2008). Learning OpenCV: Computer Vision with the OpenCV Library. O’Reilly Media