Computer vision is the eyes of the machine. AI models are built to recreate living beings' capability of looking at the world around them and interpreting and understanding it. Machines do this by analysing images, videos, and objects around them. Recent developments like Tesla's Optimus Robot and Full-Self Driving majorly relied on computer vision for object detection and image tracking. Even 2D to 3D models use computer vision for image analysis and interpretation.

The purpose of Computer Vision (CV) is to allow machines to obtain valuable information from their surroundings, by analyzing visual data that can be provided by different sources such as digital images and videos. The nature of such information depends on the final goal of the machine. Think, for example, of self-driving cars. A CV module that is capable of detecting in real-time objects that appear in front of the car is essential to avoid accidents. On the other hand, a robot that has to give directions to people inside a railway station can change the way of speaking based on whether the listener is a child or an adult.

Computer vision is the ability of any computer to see and understand the world and make decisions based on their visual insights and rational understanding. In simple words, it automates and augments human sight in computers. Video analytics or video intelligence powered by computer vision- received by categorizing and identifying the objects in the video with the help of bounding boxes are revolutionizing businesses and empowering them to mitigate risk, automate surveillance, superfine security and help them achieve operational efficiency. The advances in computer vision dominated the year 2021. Let's explore how it is going to perform in the upcoming year and the top 10 trends that are considered to lead the tech race during 2022.