What is computer vision? Some real-world examples, applications & advantages

What is computer vision? Some real-world examples,  applications & advantages

The solution that anchors AI to permit computers to obtain noteworthy information from digital videos and images and other visual inputs is called computer vision. The insights gathered through computer vision are used for taking automated actions.

Computer vision plays a crucial role in applications like face recognition, shape segmentation, material detection, etc. These applications will enable many devices and equipment we use on a daily basis to be smarter, more functional and better. For example, having a CV in a surveillance camera can help automatically detect unusual events and notify them.

According to Allied Market Research, the international CV market size in 2020 valued at approximately $9.45Bn. It is forecasted to reach around $41.11Bn by 2030 and register a 16.0% of CAGR from 2020-2030.   

In this blog, we will discuss computer vision in detail, its applications, advantages and examples. 

Computer Vision

In AI, computer vision enables systems and computers to derive worthwhile data from visual inputs, including digital videos and images. Computer vision is done to make recommendations and take actions depending on the data. Just like AI helps computer systems think, computer vision similarly helps them to witness, observe, and understand. 

Computer vision functions similarly to human vision. However, humans have a headstart as they have the benefit of a lifetime to train to tell articles apart, the farness of the objects and whether it’s still or moving and tell whether anything is wrong with the image.  Computer vision coaches AI machines for performing these functions in lesser time with algorithms, data and cameras instead of optic nerves, the visual cortex and retinas. 

Computer visions need to perform such functions in lesser time as it is used for training systems for inspecting products or monitoring production assets for analysing innumerable processes or products minutely, noticing their imperceptible issues and defects, which surpasses human capabilities. 

Computer vision is used in different industries, from utilities and energy to automotive and manufacturing. According to Blippar, it is estimated that the market for computer vision will continue to grow and reach approximately $48.6Bn (US) by FY 2022. The computer vision field has flourished with new algorithms and hardware, and the accuracy level of object identification has improved. The accuracy percentage has increased from 50% to 99% in less than a decade, making it more precise than a human vision at instantly reacting to visible inputs.

In order to make computer vision truly effective large databases are essential. It is because such solutions investigate data repeatedly till it acquires all potential insights needed for the assigned task. A computer, for instance, is trained to investigate healthy crops and requires to see a vast array of visual input references associated with animals, farmland and crops as well as other related objects. Only after investigating the visual references can it differentiate among unhealthy crops, detect animals and other pests amidst the crops, gauge the quality of farmland and so on. 

Some eminent examples of computer vision

1. 3D Photo of Facebook

Meta, earlier called Facebook, is a technology giant that also traversed its journey into computer vision to function several exciting applications. 2D pictures conversion to 3D models is one of them. 

Introduced in 2018, 3D Photo of Facebook initially needed smartphones associated with dual cameras for generating 3D pictures and creating depth maps. 3D Photos have the capability of converting two-dimensional pictures to 3D images. By this, users could scroll, tilt and rotate smartphones to view these images from various angles. Using machine learning, objects’ 3D shapes are extrapolated and depicted in the pictures. It is via this procedure that the 3D effect of a realistic look could be applied in the pictures. 

2. Google Translate

Google, the technology leader in 2015, launched an instantaneous translation service in which computer vision is leveraged via smartphone cameras. The key system, “Neural Machine Translation”, drives accurate and instant translation based on computer vision. It was included in the web results of Google translate in 2016. 

When you open the app on internet-enabled systems having cameras, the cameras can detect every text of the real world. The app can automatically detect texts and translate them into other languages according to the user’s choice. An individual, for instance, can point at any poster written in any language and read what the poster is saying in a language familiar to the user.

3. Faceapp

Faceapp is a famous application for image manipulation that alters human faces’ visual inputs to change age, gender, and other features. Such is attained via “deep convolutional generative adversarial networks”, which is computer vision’s specific subtype. 

4. Yolo

“You only look once” in short, YOLO is basically an object-detection model (pre-trained) which leverages TL (transfer learning). Such can be used for different applications comprising enforcing guidelines of social distancing. 

YOLO algorithm is able to identify and detect objects in real-time in any visual input. Such ios are attained with the usage of convolution NN (neural networks), which can forecast various class probabilities and bounding boxes simultaneously. 

As the model’s name suggests, YOLO can detect objects easily by passing one picture through a NN only once. It can learn new things effectively and quickly, storing information in object representations and leveraging such information for object spotting. 

5. SentioScope

Sentio developed a sports and fitness tracking system called SentiScope. Its primary function is to track solutions for players of soccer by processing visual inputs in real-time from live matches. SentioScope depends on a 4K camera setup for capturing visual inputs. After that, it processes the inputs for detecting players and acquiring real-time insights from their behaviour and movement. 

Computer Vision Top Applications

Even though the capabilities of the human eyes are unbelievable; however, in recent times, computer vision is striving to catch up. The top applications of computer vision are discussed below:

1. Agriculture

Even though agriculture traditionally does not associate with avant-garde technology, the age-old tools and methodologies are steadily terminating from farmlands worldwide.  Recently, farmers are using integrating computer vision for enhanced agricultural productivity.

Brands specialised in technology associated with agriculture are evolving advanced state-of-an-art computer vision and AI models for harvesting and sowing purposes. Such is also used for detection of plant health, advanced analysis of weather and weeding.

2. Facial recognition

With the help of smartphone applications, facial recognition has been intensively used at a personal level. The public security sector is also an eminent driver for solutions related to facial recognition. Computer vision’s contentious implementation for recognising and detecting faces in public is already being applied by a few jurisdictions, while in others, it is banned. 

3. Autonomous vehicles

FY 2022 can be termed as the self-driving cars’ year. Tesla, the market leader of such, Tesla, is acing their game with the help of advanced technologies like 5G and computer vision. The vehicles use a 360-degree camera which helps classify and detect objects via computer vision.

4. Interactive entertainment

Digital entertainment is no longer associated with the viewer just sitting and participating. In recent times, interactive entertainment solutions make good use of computer vision for delivering immersive experiences. High-tech entertainment services make use of AI to permit users to have a vivid interactive experience.

5. Tracking of human pose

In order to estimate the human posture, the human pose tracking models leverage the prowess of computer vision. This capability to capture the human posture can have many utilisations in industries such as robotics, physical fitness apps, gaming and physical therapy. 

6. Interactive entertainment

The days of being a non-interactive viewer are numbered. With the help of computer vision, the viewers can now experience the media immersively. For instance, techs like google wear and Microsoft’s hololenses provide the users with the same by taking their inputs and making them feel the media instead of just viewing it.

7. Manufacturing

A lot of technological advancements have been made in the field of manufacturing; computer vision has been crucial for the same. The inspection systems for checking the product over the assembly line have been powered with computer vision to find the deformities in the product.

8. Medical imaging

Medical systems require heavy assistance from trained medical staff as they are needed to detect patterns. Computer vision has been a boon for such use cases where they easily detect such patterns without additional human guidance.

9. Education

Computer vision has created new horizons in the education sector. They have enabled the monitoring of students to ensure that no one is left behind while learning by mapping their facial gestures and body posture. Moreover, they can be used for invigilating the students during the examination to curb malpractices by constantly noting the body moments of the candidates. 

10. Retail management

Due to the pandemic in the past year, retail management has seen quite a shift in the shopping paradigm. Computer vision has been a driving force behind this; they are used to get maximum ROI and customer retention by tracking shopper activity and patterns to provide in- data.

11. Transportation 

The population and expansion of the cities have led to congested roads and unsafe on-road behaviour. Computer vision has helped prevent such cases by regulating the traffic and detecting the rule violators allowing law enforcement to curb such behaviours efficiently.

Also Read: Edge AI in Practice & Some Real-Life Examples


Computer vision can be termed as an innovative technology possessing several exciting applications. The avant-garde solution uses the information we generate daily to assist computers in seeing the world and provide insights, helping computers enhance their overall quality of life.

In 2022, groundbreaking technology is predicted to unleash several new possibilities and exciting technologies, assisting individuals in leading healthier, happier, safer lives. 

It has been witnessed that the international market for computer vision in 2020 was estimated to be approximately $11.32Bn (US). It is expected to further inflate at a CAGR of 7.3 per cent from FY 2021-2028. This is because computer vision has been profusely used in several fields, making the lives of people smoother. It has been used in several sectors such as agriculture, retail, education, transportation and many more already. The future scope of such an edge-breaking technology holds the further potential to unlock new realms.

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