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What is Computer Vision? Why is this an important technology in 2020?

In technology terms, "Vision refers systems which are able to identify items, places, things, objects or people from visual images - which are collected by a camera or sensors." It is this technology which allows your camera devices such as smartphone cameras to recognize which part of the image is a face or an object and powers technology such as Google Image Search.



Computer vision is a field of artificial intelligence that trains computers to interpret and understand the visual world. Using digital images from cameras and videos and deep learning models, machines can accurately identify and classify objects — and then react to what they “see.”


As we move in 2020, we are going to see Computer Vision equipped tools and technologies rolled out for an ever-increasing number of uses. Computer vision is also enabling face recognition, which we will hear a lot about in 2020. We have already seen how useful the technology is in controlling access to our smartphones in the case of Apple's FaceID and how Dubai airport uses it to provide a smoother customer journey.


Today, a number of factors have converged to bring about a renaissance in computer vision:


  1. Mobile technology with built-in cameras has saturated the world with photos and videos.

  2. Computing power has become more affordable and easily accessible.

  3. Hardware designed for computer vision and analysis is more widely available.

  4. New algorithms like convolutional neural networks can take advantage of the hardware and software capabilities.


The effects of these advances on the computer vision field have been interesting. Accuracy rates for object identification and classification have gone from 50 percent to 99 percent in less than a decade — and today’s systems are more accurate than humans at quickly detecting and reacting to visual inputs.




How computer vision works


Computer vision works in three basic steps:

  • Getting the image

  • Processing the image

  • Understanding the image


Today’s AI systems can go a step further and take actions based on an understanding of the image. There are many types of computer vision that are used in different ways:

  • Image segmentation partitions an image into multiple regions or pieces to be examined separately.


  • Object detection identifies a specific object in an image. Advanced object detection recognizes many objects in a single image: a football field, an offensive player, a defensive player, a ball and so on. These models use an X,Y coordinate to create a bounding box and identify everything inside the box.


  • Facial recognition is an advanced type of object detection that not only recognizes a human face in an image, but identifies a specific individual.


  • Edge detection is a technique used to identify the outside edge of an object or landscape to better identify what is in the image.


  • Pattern detection is a process of recognizing repeated shapes, colors and other visual indicators in images.


  • Image classification groups images into different categories.


  • Feature matching is a type of pattern detection that matches similarities in images to help classify them.


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