Top 4 Applications of Computer Vision in 2021

17 June 2021

Organizations everywhere are investing in computer vision to boost productivity and reduce errors. Find out different ways top brands are applying the technology to determine whether it would benefit you too. 

Computer vision has come a long way since the first field experiments were carried out 70 years ago. Then, the neural networks only sought to detect object edges and perhaps classify simple objects such as circles and squares. However, we’ve recently seen the technology become much more robust and valuable.

The levels of accuracy are much higher, meaning computer vision applications can now achieve a lot more. Indeed, today’s computer vision systems are more accurate than humans at quickly detecting and reacting to visual input.

This has led to multiple high-value use cases and applications, from recognizing faces to processing live-action in soccer matches.

So, what are the standout applications today, and how have they impacted society? We’ll find out shortly. 

First, though, a recap.

What’s Computer Vision?

As the name suggests, computer vision is a branch of computer science that enables computers to see, identify, and process images in the same way humans do.

It’s closely linked to artificial intelligence because besides seeing and identifying images, the computer must process the image to understand it and provide valuable output.

An excellent example is self-driving cars. In a typical car with a human driver behind the wheel, the driver is expected to react fast and apply the brakes if someone crosses the road. Otherwise, the car might hit the pedestrian, resulting in injury or even death. 

Computer vision, when applied to driverless cars, must be just as good. The car must not only identify pedestrians fast but also immediately engage the brakes to prevent an accident.

What Can Computer Vision Do?

Computer vision solutions can do a lot, especially with the significant growth in AI technology and the massive amounts of data available. The most advanced computer vision solutions can perform;

  • Object detection: Object detection is a computer terminology that refers to instances of semantic objects of a specific class in digital images and videos. Basically, it allows computer vision tools to identify and locate objects in an image or video.
  • Object classification: Classification means assigning objects in a photo or video to a specific class. Objects are typically classified based on previously defined classes and types.
  • Object localization: Localization comes from the word “location.” It refers to the process of identifying the location of one or more objects in an image or video and drawing an abounding box around them to help with classification.
  • Semantic segmentation: This refers to the process of partitioning a digital image into multiple segments, often to simplify or change the representation of the image into a more meaningful image or one that’s easier to analyze.

Top Computer Vision Applications 2021

Computer vision applications have grown tremendously over the past half-decade and even more during the Covid-19 period. 

The following are four of the most significant applications in 2021;

#1: Computer Vision in Retail and Commerce

Computer vision minimizes human interactions in retail stores, thus boosting safety and improving customer experience. It also improves personalization and can optimize staff scheduling. Top applications in the industry include;

  • Automating checkout: Many modern stores combine computer vision techniques with shelf sensors and deep learning to recognize shoppers, detect items in the cart, and automatically deduct charges from the shopper’s credit card. Amazon GO, Lenovo, and Alibaba all use this technology.
  • In-store navigation systems: In-store navigation systems are designed to help shoppers find the shortest route to the desired items. They depend on computer vision technology to analyze the customer’s shopping list and calculate the shortest distance to items on the list. Lowes is one of the best-known users of in-store navigation systems.

#2: Computer Vision in Education

Computer vision technology has recently found a way into classrooms where it helps teachers monitor students to prevent cheating in tests. Several schools also use this technology to assess students’ papers to minimize the load on teachers. Computer vision is also driving personalization in the classroom to boost learning outcomes. Common applications in education include;

  • Student engagement detection: Computer vision technology allows educators to gauge student mood and behavior to determine whether the student is engaged or distracted. This applies in both physical classrooms and online education. Emotuit and the Little Dragon are two such technologies that help educators to measure learner engagement.
  • Attendance monitoring: Vision-powered cameras are also helping schools and educators to find out who’s attended class and who’s missing. More importantly, such tools can help educators identify students who might be cheating during a test. Two popular solutions here are ProctorU and Respondus Monitor.

#3: Computer Vision Applications in Healthcare

The digital revolution in the healthcare industry has artificial intelligence at its center, and computer vision is currently one of the most exciting tools in the sector. Two standout applications of the technology in healthcare are;

  • Medical image analysis: Computer vision technology has transformed radiology by helping healthcare providers more accurately interpret X-ray, CT scans, and MRIs. The technology is also valuable in analyzing microscopic images during brain, lung, and lung scans.
  • Surgical simulation and assistance: Solutions such as Proprio Vision combine ML, VR, and computer vision to create 3D visualizations to assist surgeons in the operating room. Another increasingly popular computer vision tool is Touch Surgery which provides a detailed guide to surgical procedures.

#4: Computer Vision in Manufacturing and Mining

Finally, computer vision also has several applications in manufacturing and mining. In these two industries, it primarily boosts automation in quality control to boost accuracy and increase productivity. Leading manufacturing companies are also using computer vision to cut inspection time and minimize safety risks. Known applications include;

  • Advanced quality control: Pharma Packaging Systems is an excellent example here. It helps drug manufacturers automatically count tablets or capsules on production lines, thus boosting productivity. Another computer vision tool, WebSpector, was recently built to help with surface inspections by identifying defects and classifying errors by type and grade.
  • Predictive maintenance: FANUC’s Zero DownTime is perhaps the best example here. It takes photos and collects metadata to help identify potential problems early, thus facilitating predictive maintenance.

Other Applications

Computer vision has many other applications spanning multiple industries such as agriculture, aviation, fitness, and sports. Contact NIX Solutions if you’d like to learn more.