Computer vision mimics human visual perception to help machines ‘see’
Whenever a machine processes raw, visual input, it is using computer vision. The subfield of computer science aims to enable computers to view, process and understand images in the same way that humans do. Due to the necessity for interpretation and analysis, computer vision is closely linked to artificial intelligence. It was first explored by academic institutions in the 1960s as a stepping stone to the creation of intelligent robots.
Computer vision is not just about ‘seeing’ – it is concerned with extracting information from visual data. This data can be a barcode, a video, a still image or a real world environment. Instead of replicating human eyes, it mimics the part of the human that handles information from images. For example, a computer vision system could create a 3D model from a 2D image, which is particularly useful in applications where machines need to perceive image depth and location. Other methods include feature detection, motion estimation, object tracking, and classification.
The improvement of computer vision is one of the most important technological developments in intelligent machines. Applications of computer vision include self driving vehicles, medical imaging, surveillance, retail, and supply chain management across industries. One fundamental aspect of computer vision is image recognition, which is a wide reaching and vital capability across all sectors.
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