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Today, I would like to recommend a latest overview of computer vision methods. This review details various concepts and technical knowledge related to machine learning, deep learning, and computer vision in the current field of computer vision, which is worth a look!
Computer vision is a science that studies how to make machines “see”. More specifically, it refers to using cameras and computers to replace human eyes for tasks such as recognition, tracking, and measurement of targets, and further performing image processing to make the images processed by computers more suitable for human observation or transmission to instruments for detection. As a scientific discipline, computer vision studies related theories and technologies, attempting to establish artificial intelligence systems that can extract ‘information’ from images or multidimensional data.
Computer vision was born in 1966 from the “the summer vision project” of the MIT AI Group. At that time, other branches of artificial intelligence had already made some preliminary achievements. Since humans can easily perform visual cognition, MIT professors hoped to solve computer vision problems through a summer project. Of course, computer vision was not solved in one summer, but after more than 50 years of development, computer vision has become a very active research field. Today, over 70% of data on the internet is images/videos, and the number of surveillance cameras worldwide has exceeded the population, generating over eight hundred million hours of surveillance video data each day. Such a massive amount of data urgently requires automated visual understanding and analysis technologies.
In this article, the author aims to give you a general understanding of all the different technologies in this discipline and their respective uses. Although some of the names of these fields may seem daunting, we will find that due to technological advancements, many areas have become ubiquitous in our daily lives, while technologies from other fields are readily accessible and can be adopted by the public. Finally, it should be noted that the order of discussion of CV methods in this overview is roughly presented in decreasing order of maturity.
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