Computer vision is a field of study within AI that focuses on enabling machines to recognize and understand digital images and video. It involves the use of algorithms to analyze and interpret visual data from the real world, such as images or videos captured by cameras, in order to extract useful information from them.
Computer vision has a wide range of applications, such as in self-driving cars, surveillance systems, medical imaging, face recognition, object detection, and image classification. It relies on a variety of techniques, such as feature extraction, object recognition, object tracking, and machine learning.
Computer vision algorithms use mathematical models and statistical methods to identify patterns and features in the visual data, and then make decisions based on this information. Some of the key challenges in computer vision include dealing with variations in lighting, orientation, and scale, as well as handling noisy or incomplete data.