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Seven Examples of How Computer Vision Could Add Value to Businesses

Oleksii Druzhynin

Lead Software Engineer, EPAM US

We’re in the midst of an AI revolution, and the technology already has many different proven applications across industries like healthcare, automotive, oil and gas, and finance. There are several fields under the AI umbrella, including one of the most rapidly evolving fields today – computer vision (CV).

What is Computer Vision?

One of the most significant untapped resources at a business’ disposal is finding value from the various forms of unstructured data available. When machine learning and deep learning algorithms are applied to CV, this technology can mimic human vision functions to identify, process and analyze images or videos, giving companies unprecedented insights and unlocking completely new service opportunities.

CV is expected to grow from $1.1B in 2016 to $26B or even approximately $50B by 2025, according to some reports. The main drivers for this growth include supply chain object detection, medical image analysis, augmented and virtual reality, and more. 

Potential Computer Vision Use Cases at a Glance

Here are some of the most interesting use cases where businesses can start to ideate and consider applying CV technology in the near future:

  • Improving Media Consumer Experiences. Media and entertainment has some of the more well-developed examples of CV on the market—from deep fake videos to realistic avatars. Another practical use case that media and entertainment companies are exploring includes using CV and deep learning solutions to sort through metadata and analyze video content, which have the potential to completely optimize the entire viewer experience. In fact, there are minimum viable projects (MVPs) for any task related to transitions in video content that ensure companies serve up the most relevant content at the right time.
  • Optimizing the Entire Supply Chain. Today’s consumers have extremely high expectations. So, there’s little room for error in supply chain management. With CV, companies could have the ability to monitor parts of the supply chain in real-time. CV can help improve accuracy in process control with image recognition, such as enhancing product visibility, counting empty bins and detecting lost inventory. 
  • Evolving Fitness Activity Tracking. CV can completely change the fitness game. For example, fitness centers can explore a computer vision-based workout tracker that automatically captures exercise statistics across the full spectrum of gym activities, all through a camera. The idea is to enable a holistic workout experience that goes beyond what exercise trackers are currently capable of.
  • Developing a New Era of Retail. There are so many ways that CV can completely transform retail, and companies like Amazon Go are already leveraging CV in stores. Imagine a brand new in-store grocery shopping experience without lines or checkouts, where you can freely grab your items from the supermarket shelf and leave because CV has processed your purchase. Or, customers could try on virtual clothes, for example, with AR/VR technologies before they buy. 
  • Building the Lab of the Future. In R&D, AI is being actively explored to build the research lab of the future, which will be full of smart technologies. In a clinical setting, CV could be used to sift through massive amounts of biological and outcomes data and identify important patterns or characteristics, potentially saving time and money throughout the drug discovery process.
  • Creating More Seamless Transportation. Mobility services are evolving fast thanks to new technologies. With autonomous vehicles already being tested in select environments, one way that CV could be applied to transportation is obstacle detection in vehicles, which can help avoid collision and calculate potential behavior of other vehicles to plan optimal routes. However, self-driving cars could take decades to become mainstream, making CV a futuristic application in this case.
  • Providing More Efficient Quality Assurance. Many factory jobs that humans perform could easily become more efficient and safer by employing CV machines. For example, many manufacturing jobs currently require manual quality control to identify defects, which can sometimes be dangerous. Additionally, CV can help track defective or contaminated products back to the source. A combination of real-time cameras and video analytics adds greater efficiency and improved safety in the quality assurance process. 
Realizing the Business Benefits of Computer Vision: Next Steps

The possibilities and applications of CV are vast. So, what’s a practical first step for your business to benefit from these growing CV capabilities? You need to start by identifying how specifically CV will help support your business’s goals and objectives, and understand the full scope of how it may impact your operations. After receiving buy-in from key stakeholders, you’ll need to find the right resources and expertise to properly execute these ideas.

Few companies have the in-house capabilities to develop CV applications in order to harness the full benefits. According to Forrester, “One key factor to success in the CV world is to bring multi-disciplinary expertise under the same roof. You need to have traditional image processing experts, deep learning scientists, embedded and imaging hardware engineers, as well as big data specialists in your team to execute groundbreaking products or offer competitive services.”

Leveraging established research and development centers to experiment before bringing a new technology to market is another important factor when ideating and building CV solutions. When companies attempt to harness emerging technologies without these key requirements, projects often fail. Research and development is another critical component to developing successful CV solutions. Ultimately, it’s critical to ensure that you are armed with all the necessary tools before diving in and implementing CV so that you can achieve its potential value.

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