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10 minutes read

What Is a Computer Vision Engineer?

By Jonathan Tarud
By Jonathan Tarud
10 minutes read

What is a computer vision engineer? If you’re interested in Artificial Intelligence, Augmented Reality, and Machine Learning this topic might be interesting for you. This is a good question, and while the tasks undertaken by a computer vision engineer are complex and challenging, the job description for this professional is simple. In the simplest terms, they work to help computers see.

However, computer vision is more complex than simple sight. This research area also seeks to create understanding and analysis of visual stimuli much like the way the average human visual system sees the world. The potential applications of successful computer vision would have large implications for Artificial Intelligence, medicine, defense, and many other aspects of human life. 

Let’s get a better understanding of what computer vision is, why we think it is important to study and research, and finally, what computer vision engineers work on. 

What Is Computer Vision?

Computer vision is a field of computer science that concerns itself with studying, researching, and attempting to develop methods that allow computers to see and understand visual information using logical thinking to solve real-world problems. On the surface, it would seem as if this problem were simple; after all, even children and animals are proficient at it. 

However, this problem is still largely unsolved. There are many reasons why we have yet to be successful, but the main reason is that biological vision is extremely complex, and despite the best efforts of our most talented medical researchers, we only have a limited understanding of it. This lack of understanding is compounded by the immense complexities of programming accurate visual perception in a dynamic and nearly infinitely varying environment that is our physical world. 

Computers work well in tight, well-defined problems. Despite our best efforts and research into Artificial Intelligence, open, unbounded, complex problems like true vision present difficulties for computers. While true vision continues to elude researchers and computer scientists, there are tasks that can be completed successfully and accurately.

Computer Vision Tasks in the Real-World

Computer vision solutions are used every day in a number of different ways. In fact, it is likely that you have come across some form of this technology in your daily life. Do you use Snapchat? Do you like to add filters to your pictures that allow you to put on dog ears or other funny faces? This is a good example of this technology. 

If you have a newer iPhone model, your phone likely has facial recognition features that help you unlock your phone and set up secure Apple payments. This is another example. If you’ve used either of these two common examples of this technology, you will know that while they work well, they are far from seamless. This technology has come a long way in object detection and making accurate conclusions, but it is still far from perfect. 

Since true vision is still more science fiction than actual reality, vision systems need to rely on Deep Learning, Machine Learning models, neural networks, and other computer vision libraries in an attempt to recognize objects in digital images. Vision systems have become adept at the following recognition tasks:

  • Classification – what category does this object belong to?
  • Identification – what type of object is this?
  • Verification – is this object present in the image?
  • Detection – where are the objects in this image?
  • Landmark detection – what are the key points in this image?
  • Segmentation – which pixels belong to this object within the image?
  • Recognition – which objects are present in this image, and where are they?

Computer vision has been used with success in the following fields and applications:

  • Retail
  • Machine inspection
  • Medical imaging 
  • Fingerprint recognition
  • Biometrics
  • Facial recognition
  • Surveillance 
  • Motion capture
  • Match move (used to merge CGI with actors in movies)

Why Is Computer Vision Important?

While most of the vision systems that we are familiar with are fun (like Snapchat filters), this technology has the capability to change the world as we know it. Self-driving cars, for example, rely on it for determining distances and recognizing stop signs and traffic lights. Self-driving cars are still being developed, but when this technology is perfected, it will revolutionize the way we drive, if we even continue to drive at all. This will have a large impact on our emissions, and our global climate, and can open up transportation access to millions of people. 

This technology can also be utilized in IoT MedTech systems to help spot cancerous moles on the skin or find medical issues in X-rays and MRI scans with greater accuracy than medical experts. It is already being used by some medical systems, but as vision capabilities improve, it will become more prevalent and more successful at spotting trouble earlier than the human eye. This could help us lead healthier and longer lives. 

Computer vision research is important to our global society because it has nearly limitless potential. The long-term success and improvements to this technology are deeply connected to Artificial Intelligence. It will likely not exist until Artificial General Intelligence (AI with the ability to reason like a human) is created. 

What Does a Computer Vision Engineer Do?

Now that we understand what computer vision is, where this technology is currently being developed, how it is being used in real-world applications, and why it is so important, we can look at the role of computer vision engineers. This tech professional applies computer vision research and works closely with object-oriented software to handle the processing and analysis of large data populations in an effort to support the automation of predictive decision-making through visuals.

After reading the information we have presented thus far, you might assume that one of these engineers spends their time researching biological vision, implementing Machine Learning primitives, Deep Learning, and AI. While some engineers are undoubtedly hard at work researching and studying these topics for the pure purpose of tech advancement, the grand majority of these engineering jobs are in electronics, eCommerce, electrical engineering, and aerospace applications.

That is not to say that these positions do not require research and study to make improvements to computer vision systems, but the majority of these professionals are not working full-time on solving the problem of true computer vision and general AI. The majority of computer vision engineer jobs will focus on app development, computer vision systems improvements, and writing algorithms. 

What Skills Does a Computer Vision Engineer Need to Have?

This is a complex job that combines high levels of knowledge from a few different disciplines, primarily mathematics and computer science. With that in mind, if you’re interested in becoming a computer vision engineer, you’ll need to have a strong knowledge of mathematics, specifically data science, calculus, and linear algebra. It also requires in-depth knowledge of linear algebra libraries, ML libraries, and programming languages such as C++, Python, Java. Other skills that are required for this job include:

  • Ability to develop image analysis algorithms
  • Ability to develop Deep Learning frameworks to solve problems
  • Design and create platforms for image processing and visualization
  • Knowledge of computer vision libraries
  • Understanding of dataflow programming
  • Database management skills
  • Software engineering experience
  • Critical thinking skills
  • Excellent communication skills

The above software skills are the most common and important basic skills you will need to get a basic entry-level computer vision engineer job. Obviously, there are higher positions in this field that require more advanced skills and knowledge. 

If you’re looking for a job in this field, you’ll also likely need at least a bachelor’s degree in mathematics, Machine Learning, information systems, information technology, or other related fields of study. Many of these jobs will also require applicants to possess a master’s degree as well. This is a highly skilled position, and companies want to hire the most qualified, talented, and detail-oriented applicants. 

What Is the Job Outlook for Computer Vision Engineering?

The job outlook for computer vision engineers, like a lot of other information technology jobs, is very positive. This technology is only going to continue to improve and be adopted by more companies for use in more applications. The field of computer vision, specifically, and technology generally, is only going to create more jobs and opportunities for people as time passes. 

Currently, the average computer vision engineer in the United States makes an average salary of 122,000 dollars. According to the United States Bureau of Labor Statistics, jobs for computer and information research scientists are expected to grow by 15% between 2019 and 2029. This growth rate far outpaces all other occupations in the American economy. However, it is important to note that computer and information research science is a small field. A 15% growth rate over the next decade only accounts for 5,000 jobs created. Still, while that figure may seem small, it is important to remember that this is a highly specialized field, and the number of qualified candidates for these jobs remains low too. 

If you’re interested in the field of computer vision engineering, there has never been a better time to get the various software skills and education required to be competitive in the job market. These positions pay well, they allow people to work on interesting projects with real-world applications, and there is job growth at a rate that is unmatched by any other sector in the American economy. 

Why Should Businesses be Interested In Computer Vision?

All businesses should be interested in computer vision. Not only are cameras getting more sophisticated, but they are also getting cheaper and more ubiquitous. The result is that there are more potential applications for computer vision across every industry.

Chances are very good that your business could use computer vision to its benefit. Whether your organization uses computer vision to improve the products and services it offers consumers, optimize business operations, or just improve the security of its business locations, there are several beneficial ways this technology can be utilized.

As computer vision technology continues to evolve and improve, it will be difficult for organizations to ignore it. Now is an advantageous time for companies to begin considering the different ways they can utilize this technology.

Final Thoughts

Computer vision is a very interesting and exciting field of study. While true vision, much like true general AI, has yet to be created, there are many beneficial and entertaining applications for this technology. Self-driving cars are not a long way off. This application of the technology is almost ready for widespread use by consumers. This technology is also already helping medical professionals make better decisions and spot health problems sooner, and it is fun to play with on our smartphones. 

If you’re interested in this field, there is almost no limit to the type of projects you can work on. This is a fast-growing field of study, and the job market is growing rapidly. 

We hope this article has answered your questions about computer science and the role of computer vision engineers in it.

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