Computer vision is a field of artificial intelligence that trains computers to interpret and master the visual world. Utilizing digital photos from cameras as well as video and deep learning models, machines can accurately identify and classify objects, and then react to what they “see” usually called computer vision algorithms. After understanding what computer vision is, here’s its history. Early experiments in computer vision took place in the 1950s, using some of the early neural networks to identify the edges of an object and sorting simple objects into sections such as circles and squares. In the 1970s, the foremost commercial use of computer vision analyzed typed or handwritten text operating visual character distinction. These advances are used to interpret written readings that are useful and helpful for blind people.
As the internet matured in the 1990s, it created a large collection of images available online that were useful for the analysis and development of facial recognition programs. This growing data set enables machines to identify specific people in images and videos. Today, several aspects are coming together to bring about a renaissance in computer vision:
1. Mobile technology with embedded cameras with images and videos.
2. Computing resources are abundant and more affordable and easily accessible.
3. Hardware designed for the needs of computer vision and more computer analysis.
4. New algorithms such as convolutional neural networks can utilize and use hardware and software expertise.
The effect of the development of computer vision is enormous. The level of identification, accuracy, and classification of objects has increased from 50% to 99% in less than a decade and makes this system more accurate than humans in detecting and reacting faster to visual input. How does computer vision work, before that computer vision itself was used to detect faces to process their visualization, computer vision surpasses human visuals in many areas.
