![]() What distinguished computer vision from the prevalent field of digital image processing at that time was a desire to extract three-dimensional structure from images with the goal of achieving full scene understanding. ![]() In 1966, it was believed that this could be achieved through a summer project, by attaching a camera to a computer and having it "describe what it saw". It was meant to mimic the human visual system, as a stepping stone to endowing robots with intelligent behavior. In the late 1960s, computer vision began at universities which were pioneering artificial intelligence. As a technological discipline, computer vision seeks to apply its theories and models for the construction of computer vision systems. The image data can take many forms, such as video sequences, views from multiple cameras, or multi-dimensional data from a medical scanner. It involves the development of a theoretical and algorithmic basis to achieve automatic visual understanding." As a scientific discipline, computer vision is concerned with the theory behind artificial systems that extract information from images. "Computer vision is concerned with the automatic extraction, analysis and understanding of useful information from a single image or a sequence of images. From the perspective of engineering, it seeks to automate tasks that the human visual system can do. Ĭomputer vision is an interdisciplinary field that deals with how computers can be made to gain high-level understanding from digital images or videos. 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. The technological discipline of computer vision seeks to apply its theories and models to the construction of computer vision systems. 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 device. The scientific discipline of computer vision is concerned with the theory behind artificial systems that extract information from images. 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. 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. Ĭomputer 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. ![]() From the perspective of engineering, it seeks to understand and automate tasks that the human visual system can do. It is doubtful, however, that these are entirely successful.Output of DenseCap "dense captioning" software, analysing a photograph of a man riding an elephantĬomputer vision is an interdisciplinary scientific field that deals with how computers can gain high-level understanding from digital images or videos. Some responses to this problem are available. Hence, for any one individual it is the case that her relative standing is beyond her control. But no individual controls the choices of all others. ![]() Her relative standing, something with which egalitarians ought to be concerned, is determined by her choices in conjunction with the choices of all others. The reason is that while she has in one sense chosen her (new) welfare level, she has not chosen to be worse off than others. However, even if we can say that the person's new welfare level is justified in absolute terms, it is less clear that her now being worse off than others, is justified (a similar idea is explored by Susan Hurley). If a person responsibly acts in a way that brings her welfare level below that of others, this is justified according to the theory. This article argues that there is a tension in standard luck egalitarian theory between justifying absolute and comparative welfare levels. According to luck egalitarianism it is bad or unjust if someone is worse off than another through no fault or choice of her own.
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