Constructing computer vision systems seemed to be an unrealistic task for scientists, at the beginning of the 20th century. Neither engineers nor data analysts were fully equipped to extract information from images, let alone videos. The ability to see and recognize objects is a natural and familiar opportunity for a person. However, for the computer so far – this is an extremely difficult task.

Have we really come across CV in our day to day life??? Indeed, we have!!!!

The term computer vision hasn’t really appeared in the popular media that much until recently. Part of that is because when something became successful, it got renamed. Like bar code scanning is an instance of computer vision – it is being used extensively to make online payments through various mobile apps on daily basis.

So basically, Computer vision is a field of computer science that works on enabling computers to see, identify and process images in the same way that human vision does, and then provide appropriate output. It is almost like imparting human intelligence and instincts to a computer.

The field of application of computer vision and image understanding is very wide. For instance, modern computer vision with ML algorithms helps to facilitate agriculture, retail shopping, post services etc.

In today’s world when the world is going through a rough phase, adopting Computer Vision & ML to minimize human contact & intervention is proving to be a boon.

Let us look at some of the areas where CV is being used.


Computer vision techniques are used in autonomous vehicles to detect pedestrians or other objects Computer Vision in autonomous cars can lead to the designing and development of advanced and next-gen vehicles that can overcome driving obstacles while keeping passengers safe.

Such cars can transport passengers to their destination eliminating human intervention.

Cars are equipped with sensors and software that can detect 360 degrees of movements of pedestrians, cyclists, vehicles, road work and other objects from up to three football fields away.

It is able to follow traffic flow and regulations, and detects obstacles in its way.

The company claims to use deep networks for prediction, planning, mapping and simulation to train the vehicles to maneuver through different situations such as construction sites, give way for emergency vehicles, make room to cars that are parking, and stop for crossing pedestrians.


For a long time now, computer-supported medical images are being used for a diagnosis like CT scans, X-rays, etc. Furthermore, recent developments in computer vision technologies allow doctors to understand them better by converting them into 3d interactive models and make their interpretation easy.

If we look at the most recent use case of computer vision then we will find it is detecting COVID-19 cases using a chest x-ray. It can further be used efficiently to distinguish Covid-19 from community-acquired pneumonia.

But medical imaging is not the only area where computer vision can play an important role. For instance, with respect to visually impaired people, there are setups that assist them to navigate indoor environments safely. These systems can place the person and the surrounding objects in a floor plan, among other things, to provide a visual experience in real time.

Gaze tracking and eye area analysis can be used to detect early cognitive impairments such as autism or dyslexia in children, which are highly correlated with unusual gaze behavior.


What do you feel are the most urgent challenges within the food and agricultural industries? The dairy industry is under constant pressure to lower prices, with many farmers famously reporting losses on the cost of production. A cow’s milk production can be directly correlated to its state of wellbeing, and as such maintaining good body condition is key to maximizing yield. Reliable detection of lameness has also been shown to be non-trivial as livestock will often attempt to mask the symptoms from human observers. How can these problems be solved with technology?

Commercial computer vision systems are currently under development to autonomously examine, record and report dairy cattle condition repeatedly and over prolonged periods.

How can these problems be solved with technology? Commercial computer vision systems are currently under development to autonomously examine, record and report dairy cattle condition repeatedly and over prolonged periods.

The advantages of such systems are three-fold:

  1. The dairy farmer can maintain an accurate and lasting record of herd condition
  2. The measurements of said condition are objective and not subject to human influence
  3. The animals themselves are not influenced by the presence of humans, so are less likely to attempt to mask symptoms, thus allowing earlier and more accurate detection of lameness.


Although photographic cameras capable of face detection for the purpose of performing auto focus have been around since the mid-2000s, yet more impressive results in facial recognition have been achieved in recent years. The most common (and controversial) application is perhaps to recognize a person in an image or video.

This is especially so with security systems like intrusion detection system in a restricted area, but it also comes into play in social media when adding filters to faces, in photo management systems to be able to search by person, or even in preventing a person from voting more than once in an electoral process.

Facial recognition can also be used in a more sophisticated way, such as to recognize emotions in facial expressions.


A visual search engine is able to retrieve images that meet certain content criteria. Searching for keywords is a common use case, but sometimes we can present a source image and request that similar images be found. In the e-commerce market, if you need outfit ideas inspired by your wardrobe (for example, you want to find new ways to wear your favorite jeans or blazer), you can take a photo of the item and the Visual search engine will return in the outfit ideas that include compatible clothing items you can ultimately buy. Visual search for online shopping is one of the fastest-growing trends in recent years.

Should we be afraid of CV?

But having realized the positive aspects of CV, how it is able to ease our lives, there is also a negative side to it. We should also be aware of the threats posed by CV applications on our day to day life and privacy for instance in London and Beijing all of your movements everything you do in the city is recorded by surveillance cameras which are there at every street corner in every public place you know.

Latest technologies like facial recognition can find you out in a crowd and all security cameras are equipped with it. What would it look like to live in a city like this where everything you do – if you go to the store with your friend or if you go out to lunch or as you’re going to work or coming home, it’s all being watched and monitored by your government and with these kinds of visual algorithms it’s possible that everything you do could be logged in the large database somewhere and it’s not just governments that are interested in this technology but also some of the largest tech companies. They already track basically everything you do online because their whole business model is selling your personal information to advertisers.

Do you really want them to watch everything you do offline as well?

Computer vision that has potential for good in our society is being co-opted to invade privacy, sell advertising and maintain these structures of power – the large tech companies.

The question is to how can we break out of this cycle – how we can use CV for the good, keeping the privacy of the customers/users safeguarded because only then we will be able to truly realize the power of technology as a force for good in our world.