The term Computer Vision (CV) may sound like it was taken from a futuristic sci-fi movie. But, actually, it wasn’t. Computer Vision is an absolute reality which actually penetrates deep into our lives. From industrial applications and navigation to medical analysis and facial recognition algorithms – this is where you can find CV.
Thanks to CV and touch recognition patterns being introduced to mobile devices those who are visually impaired or totally blind (about 300 million people worldwide), can now experience visual content on Facebook in the same way as sighted people do.
In the following paragraphs, we will give you a deeper insight on what it is, what are its advantages and areas of application.
What is Computer Vision?
In simple words, term Computer Vision means programming computers to “see” the outside world in more or less the same way as humans do. And, obviously, CV can’t be done without artificial intelligence (or AI), and machine learning (or ML). Cameras programmed in the right way and vision processing units are a must as well.
Computer Vision works as a basis for a wide range of industrial robots, smart cameras, pedestrian detection, fingerprint recognition, augmented reality, virtual reality, etc. And it is getting more and more popular. For instance, the facial recognition global revenue was less than 200 million USD in 2015. By 2020, it is expected to reach somewhere around 500 million USD.
Bridge From CV to Augmented & Virtual Reality
In order to allow the computer’s camera to sort out the visual world, it is essential to program it in a special way. There are 4 main methods used to deal with this challenge: blob detection, template matching, edge detection, and scale space. And here are some details about each of them.
Blob detection
The mission of the blob detection is to check the image and to determine different regions in it. To determine the regions, it looks for areas with different colors and brightness — they must contrast to the surroundings. Blob detection is often used for matching images and, therefore, finding differences between them. Image retrieval systems, such as Google, are a great example in this case.
Template matching
This technique is all about finding those pieces of an image which match the given template. Template matching is widely used in facial recognition software — for instance, Facebook already has a facial recognition feature.
Edge detection
The edge detection method implies finding points in an image where the brightness changes significantly or even ceases. Those line segments which become visible after these points get organized, are called edges. They can be very useful when it is essential to determine the object’s specific features (corners, curves, lines, etc.). Edge detection is widely used in AR and VR — for instance, vorpX allows users to play non-VR games using their Oculus Rift, and edge detection is among those features which make this possible.
Scale space
Scale space is used for processing the multi-scale reality of the structures of the image. If there is no data for determining the scales (already available), the image is broken down into the basic elements. In this way, it is possible to understand the properties of the given data set. For example, the scale space approach can be used for analyzing handwritten documents, which is a great thing for digital libraries.
What CV means to AR and VR
With all the above-mentioned techniques, Computer Vision is absolutely crucial for the development of Virtual Reality and Augmented Reality. For example, Computer Vision can help to understand which objects can improve the experience, and which of them shouldn’t be considered.
How Can It Improve Your Business?
A business can benefit significantly from using CV, and there are several potential advantages:
Computer Vision can help to develop great AR or VR apps
This advantage can mean something to you not only in case your business is all about VR and AR technologies and app development. Virtually any business (retail, medical, etc.) can be improved with the help of a VR or AR app, and, as we already mentioned before, really cool apps are simply impossible without Computer Vision.
Reduction of costs
This advantage works great for retail businesses and manufacturers. CV can help to eliminate faulty products both in stores and shops, and, therefore, save the time of your employees and machines they may use. And, obviously, this means that the costs on production (or other activities) will reduce — you won’t have to do the same things several times, as everything will be flawless from the very beginning. In addition, you won’t need as many workers in the quality control department as before. Some of them will be able to switch to other tasks.
Another advantage related to the reduction of costs is that you will be able to save a bit on training the new staff — machines and cameras (for instance, at factories) have to be programmed only once, while employees tend to change from time to time.
Accuracy and reliability
People tend to get tired, especially when they do a routine job at a factory for a long time. However, CV-based products can work without having breaks, and while a human eye can miss small defect, a well-programmed camera will never do this. This is especially important in case you produce something in large quantities — for example, you need to check each and every bottle label that comes out of the production line.
Increased productivity
Since standard visual checks in industrial sector are done not by people, but by reliable and fast computers, Computer Vision can accelerate and simplify the production processes. As a result, company will be able to produce more products than before.
How to incorporate it in your business
Implementing Computer Vision solutions requires a careful strategy behind. So, before incorporating CV in your business, go for user requirement and competition analysis.
- How can such innovation improve your customers’ experience?
- Do they actually need it?
- Do your competitors use Computer Vision or not?
- If yes, what are their weaknesses?
And last, but not least — how exactly Computer Vision can improve your business? After you are done with analysis, you will be able to develop a list of concrete goals and focus on them. It will be your starting point for business grow and the way to differentiate on the market.
Successful Implementation
Now it is time to talk about several examples of successful Computer Vision implementation in different industries.
Royal Mail in the UK
To simplify and speed up the delivery process, Royal Mail in the United Kingdom incorporated an automated facility in 2004. The company spent 150 million pounds, but the result was worth all the efforts and expenses — this facility allows scanning the envelopes (both their fronts and backs) and transforming the addresses into a machine-readable code. As a result, the next day delivery was enabled at scale.
Snapchat
Snapchat is one of the most popular modern apps — it boasts almost 200 million daily active users! Obviously, it would never become that demanded without augmented reality which is, in turn, based on Computer Vision. And masks and stickers are not the only augmented reality features available at Snapchat. Recently, Snapchat introduced Shoppable AR Lens feature which allows advertisers to add “Install Now”, “Buy Now” or “Watch” buttons to the branded Lenses. In this way, advertisers can bring real-life experience to their customers and, therefore, increase their loyalty and attract new clients.
Lens, a new tool offered by Pinterest, gives users an amazing opportunity — they can simply point the camera of their smartphone at any object, and then start the Pinterest search in order to find the related content. Actually, it is something like Shazam providing pictures instead of songs.
Obviously, there are much more examples of Computer Vision implementation in various industries: Amazon Go (a chain of grocery stores that allows to do shopping without standing in lines), Realeyes (a company using emotional analytics in order to test content and plan media — this is possible thanks to people sharing their cameras), ANPR Systems (used worldwide for automatic number plate recognition) and so on. And more of them are expected to arrive, as Computer Vision is used for AR and VR which are currently conquering the world.
Incorporating CV is a great idea in case you want your company to stay afloat and succeed — that’s a technology of the future, and its evolution is not going to stop. So it might be better to join it, as CV hides plenty of opportunities and advantages. Now you know more about what this technology actually is and how it can help your business to grow, but if you still have some questions or need to hire a computer vision engineer, feel free to get in touch with our team.
