Computer technology is an ever-growing field. We are witness to innovations being outdated in a matter of years — with all sorts of advancements like continuously increasing memory storage to wireless charging.
Today, humans of all ages have at least the slightest knowledge of how a computer works. There’s coding for kids now, too — we see middle schoolers learning coding languages such as Python on the regular. Technological trends such as virtual reality, mobile payment, and home technology shortly followed the surge of smartphone usage around the globe. And above all these trends, one stands out: artificial intelligence or AI.
Artificial intelligence, together with machine learning, paved the way for computer vision systems that benefit several industries today.
What is computer vision?
Computer vision is an AI field that trains computers to understand and interpret the visual world. Our human eye can only process so much information. With computer vision systems in place analyzing the world through images, industries are able to gather high-yield information faster than the human eyes could.
How does it work?
Think of a jigsaw puzzle. To solve it, you need to assemble the pieces together to form an image. This is how computer vision’s neural networks do it. Computers are able to put the parts of the images together and think on their own through a series of filtering and actions.
But remember, computers follow a unique set of processes in order to analyze huge amounts of data; so they are not given a puzzle of an image, but rather they are trained to “look” at thousands upon thousands of photos, videos, and images in order to recognize them. For example, in training a computer to recognize trees, programmers are not going to feed them images of leaves, roots, trunks, and branches that make up trees. Instead, they will upload millions of images of trees until the computer understands all the features that make up trees and recognize them right away.
Where is it used?
Computer vision is being utilized in more industries and areas that you might expect. Its core concepts are actually already integrated into products that we use on a daily basis. Here are a few examples.
The algorithms of computer vision have the ability to detect facial features in images and compare them with faces in a database. Consumer devices such as smartphones make use of computer vision systems for you to be able to unlock your phone by just staring at it. In social media, gone are the days when you had to tediously go through every photo in your album on Facebook and tag each of your friends. Facial recognition technology via computer vision already takes care of that and tags your friends automatically. Those in law enforcement also benefit from computer vision in facial recognition technology to identify perpetrators in video feeds.
Self-driving cars are able to make sense of their surroundings — read traffic signs and detect other cars, pedestrians, and objects — through computer vision. The cameras that capture images from all the angles of the car feed the computer vision software for processing. Computer vision helps self-driving cars to avoid obstacles, navigate streets and highways, and take their passengers to their destination.
Computer vision has an immense impact on health care. There’s computer vision software now that can be installed on the MRI and detect anomalies in the scans of vital organs like the liver, heart, and lungs, among others. Computer vision also enabled scientists to come up with applications to help detect cancer early. For skin cancer, for example, these tools are able to distinguish cancer lesions on the skin from non-cancerous lesions. The development of computer vision applications to detect bone and breast cancer are also ongoing.
Retailers have started adopting visual search in their online platforms to improve customer experience. Customers are now rid of the challenge posed by text-based queries and are able to use images to find the products they want. Businesses also utilize computer vision to amp up their customer engagement strategy. Chatbots can answer questions that do not take too much effort such as queries about colors, sizes, styles, etc. Through a computer vision system in place, customers can simply send a picture to a retailer’s chatbot, and then AI does its magic and answers the query.
Computer vision, indeed, has the potential to be a game-changer in every field imaginable. The average user of today benefits from computer vision applications that artificial intelligence and machine learning have made possible.