Computer Vision is a field that is the branch of computer science. It is not a new technology, it was first introduced in the year the 1950s, and its experimentation was already started, while in the 1970s it was used commercially to distinguish between typed and handwritten text.
It is called in shortened form as ‘CV’. It works like the human brain and eyes, by recognizing patterns and images, and visual data using the capturing and interpreting devices. The computer is trained on many visual data to analyze and detect the images.
Computer vision impacts AI to permit computers to get the right information from visual data like photos and videos, etc. As AI allows the system to have the capability to think, the CV allows the system to see.
There are plenty of applications for computer vision. Some of the interesting examples of Computer Vision in recent years are as follows:
Computer vision is essential to promote self-driving cars. Autonomous vehicle manufacturer such as Tesla, BMW, Volvo, and Audi uses the multi-camera setup to examine their surrounding objects, LIDAR, and ultrasonic sensors to obtain pictures from the surrounding for lane marking, traffic signs and signals, object detection for driving safely.
Google Translate is an app that Google launched from around 2015 to 2016, in which users can translate one language into another 100 other languages. The main system uses neural machine translation. Google uses computer vision as a convenient tool. It is made available offline too. The translation is done through smartphone cameras, the camera detects automatically any text or foreign language sign board. Google also uses computer vision in its Lens featured app.
It is one of the well-known examples of computer vision. It is mostly used for public security applications using facial detection, the criminal suspects can be traced and crime can be avoided to happen at that time. Facial recognition also uses deep learning and machine vision technology along with the CV. The face is captured and the further process of analysis by the system is done. China is the leading country to use facial recognition technology for preventing thefts, security, and patrolling at many places like airports, etc.
Today's Facebook known as Meta uses a feature known as Facebook 360 that was launched in 2018. One gets a 2D photo converted to the effect of a 3D photo and the user can post it on his/her page. For using this one needs to have a dual camera in the smartphone to develop 3D images and make a depth map, it is a computer vision algorithm-based feature. Users can tilt, and rotate to view this photo from different angles. A much older picture can be displayed in a 3D way. For the extrapolation of the 3D shape of objects displayed in images, machine learning is used.
Computer vision is helpful in assisting play and strategy estimation, for tracking the player's performance during sports match broadcast. On another hand, cameras are used for tracking and detecting balls moving in the games, and AI-enabled software is used for detecting the position of the player at a specific moment for better performance of the team.
One of the best examples comprises of SentioScope which is the software used for tracking players. It is helpful in fitness-based and in self-training solutions and many more. There are numerous other examples in other fields like manufacturing, agriculture, education, healthcare, etc. I conclude with today's blog. Hope you liked reading it.
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