Have you ever used the object recognition app on your smartphone, such as Google Lens? These are seemingly simple apps that tells you what the object is that the camera is facing.

You might wonder how this works: how can a phone possibly identify an object? The answer is computer vison. A long definition for computer vision is a field of Artificial Intelligence (AI) that enables computers to extract meaningful information from digital images, videos and other digital visual media and then take actions or provide recommendations to users based on that information. A simpler way of understanding computer vision is that it is a technology that enables the computer to recognize people, objects or actions, and perform actions based on that information.

Computer Vision Explained

Take a look at the image below.

As a human being, we can immediately identify this image as a flower. We know because we have seen thousands if not millions of different flowers in a variety of different contexts – from pictures and film to standing in gardens – which has helped us to build an expansive knowledge base that we can use to recognize flowers. Through our extensive exposure, we know automatically this image contains a flower, even if we might struggle to articulate how we know or the criteria we use to form this judgement.

But how does a machine recognize a flower when it has none of the knowledge or experience of a human to draw from- and this image is nothing but a bunch of numbers?

That’s where computer vision comes in. Computer vision uses algorithms that mimic the visual recognition capabilities of the human brain to interpret and give meaning to these numbers. To do so, it requires a huge amount of data – in this context, a lot of images of flowers - so that the model can be trained to capture the patterns and trends behind these numbers that enable it to recognize the target.

But this novel example of using smartphones to recognize flowers is just the beginning. Computer vision can do a whole lot more.

Computer Vision in real life

There are some promising use-cases for computer vision that promise to be revolutionary for different industries. Here are some examples that illustrate the variety of different use-cases:

Computer vision in automotive:

Computer vision is one of the core technologies powering the reality of driverless vehicles. But driving is an exceptionally complex task that requires continuous awareness, the ability to make sound judgements and react to changes in real-world conditions in fractions of a second. Computer vision is responsible for enabling the vehicle to quickly and accurately recognize objects and events in the surrounding environment and informing action based on what is detected, such as stopping if it detects a pedestrian.

Computer vision in retail, e-commerce and web search:

Have you ever been in a situation where you’ve seen a picture of an item that you like, but don’t know the brand or where to find it – and your best attempts to describe the item yield unsatisfying results? Well, tools such as Google Lens use computer vision that offer customers a completely new way to find things online using image-based search. Simply take a photo or upload an image and Google will cross reference it against their extensive database and direct you to the