Understanding computer vision
At the beginning of the 20th century, computer vision was an unrealistic dream for scholars and engineers. Back in the 1960s, the Summer Vision Project, which was assigned to undergrads, first talked about developing a computer system that will interpret the stimuli from the surroundings and respond accordingly. Another trace in the history of computer vision is provided by Larry Roberts. His thesis, ‘Machine perception of three-dimensional solids’ outlined how to “extract 3D information from 2D images or objects.” Later in the 1980s, David Marr published “Vision.
A Computational Investigation into the Human Representation and Processing of Visual Information,” which was also one of the discoveries in the history of computer vision. Since then, rigorous studies were conducted by many scientists and engineers in the field. Finally, in the 1990s, due to cheaper, high-powered supercomputers, engineers working on computer vision redirected their focus to mathematical models. With continued research and refinement, computer vision was transformed from an unrealistic idea or expectation to practical reality. But, what exactly is computer vision all about?
Computer vision: the concept
Computer vision is nothing but a scientific field that allows computers to capture, interpret, understand, and process the objects that are visually perceivable. With the help of Artificial Intelligence (AI) and deep learning models, computer vision systems are able to understand the captured digital images and react suitably.
Today, several industries are benefitting from computer vision technology. Computer vision systems serve myriad purposes, ranging from predictive maintenance to quality control and on-site safety.
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