computer vision - meaning and definition. What is computer vision
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What (who) is computer vision - definition

COMPUTERIZED INFORMATION EXTRACTION FROM IMAGES
Computer Vision; Image recognition; Computer vision systems; Image Recognition Techniques; Computational vision; Image understanding; Image Understanding; Image Recognition; Image classification; Computational Vision; Texture recognition; History of computer vision; Visual recognition software; Applications of computer vision; Computer vision intelligence; Computer visual intelligence; Image classifier; Shape recognition; Visual recognition; Image identification; Classification of images; Image-based artificial intelligence; Military applications of computer vision
  • [[DARPA]]'s Visual Media Reasoning concept video
  • Rubber artificial skin layer with the flexible structure for the shape estimation of micro-undulation surfaces
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  • Above is a silicon mold with a camera inside containing many different point markers. When this sensor is pressed against the surface the silicon deforms and the position of the point markers shifts. A computer can then take this data and determine how exactly the mold is pressed against the surface. This can be used to calibrate robotic hands in order to make sure they can grasp objects effectively.
  • Learning 3D shapes has been a challenging task in computer vision. Recent advances in [[deep learning]] have enabled researchers to build models that are able to generate and reconstruct 3D shapes from single or multi-view [[depth map]]s or silhouettes seamlessly and efficiently.<ref name="3DVAE" />

computer vision         
A branch of artificial intelligence and image processing concerned with computer processing of images from the real world. Computer vision typically requires a combination of low level image processing to enhance the image quality (e.g. remove noise, increase contrast) and higher level pattern recognition and image understanding to recognise features present in the image. Usenet newsgroup: news:comp.ai.vision. (1994-11-30)
Computer vision         
Computer vision is an interdisciplinary scientific field that deals with how computers can gain high-level understanding from digital images or videos. From the perspective of engineering, it seeks to understand and automate tasks that the human visual system can do.
image recognition         
<graphics, artificial intelligence> The identification of objects in an image. This process would probably start with image processing techniques such as noise removal, followed by (low-level) feature extraction to locate lines, regions and possibly areas with certain textures. The clever bit is to interpret collections of these shapes as single objects, e.g. cars on a road, boxes on a conveyor belt or cancerous cells on a microscope slide. One reason this is an AI problem is that an object can appear very different when viewed from different angles or under different lighting. Another problem is deciding what features belong to what object and which are background or shadows etc. The human visual system performs these tasks mostly unconsciously but a computer requires skillful programming and lots of processing power to approach human performance. (1997-07-20)

Wikipedia

Computer vision

Computer vision tasks include methods for acquiring, processing, analyzing and understanding digital images, and extraction of high-dimensional data from the real world in order to produce numerical or symbolic information, e.g. in the forms of decisions. Understanding in this context means the transformation of visual images (the input of the retina) into descriptions of the world that make sense to thought processes and can 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.

The scientific discipline of 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, multi-dimensional data from a 3D scanner, or medical scanning devices. The technological discipline of computer vision seeks to apply its theories and models to the construction of computer vision systems.

Sub-domains of computer vision include scene reconstruction, object detection, event detection, video tracking, object recognition, 3D pose estimation, learning, indexing, motion estimation, visual servoing, 3D scene modeling, and image restoration.

Adopting computer vision technology might be painstaking for organizations as there is no single point solution for it. There are very few companies that provide a unified and distributed platform or an Operating System where computer vision applications can be easily deployed and managed.

Examples of use of computer vision
1. Ko previously worked on computer vision and artificial intelligence at the Samsung Advanced Institute of Technology, but plans to carry out research into robotics after the space mission.