Introducing Computer Vision
Computer Vision, or CV, is a branch of Artificial Intelligence (AI) that teaches computers and other devices to extract meaning from digital images and video and come to conclusions based on what it sees.
So, computer Vision enables a device to observe and give meaning to the observed. The field has advanced to the point that a machine’s camera and algorithms can derive significance from a moving or static image, and in many cases, better than a human eye and brain.
Computer Vision has been used in a wide range of business sectors from healthcare to vehicle automation and from fintech to manufacturing processes.
The Growth Potential of the Computer Vision Technology Market
Computer vision is currently applied across a variety of industries such as manufacturing, marketing, healthcare, fintech and others. In 2019, the computer vision market was valued at $13.7 billion in 2019, and this figure is expected to increase up to $24.3 billion with an average growth rate of 7.7% from 2020 to 2027.
Based on the Economist Intelligence Unit survey, 75% of manufacturing companies claim that the efficiency of production and quality control have been improved due to the application of CV. Also, computer vision innovations helped to boost cost saving efforts by 10% in all sectors. Asa result of these impressive growth numbers, many companies have entered the AI space offering a range of services in addition to computer vision including data labelling and natural language processing.
Training Data for Computer Vision
Training data is the input used to train a machine. Training data will measure performance, such as accuracy or efficiency, of the algorithm used in the machine.
Good Computer Vision demands extensive and high-quality training data for accuracy. The quality and quantity of CV training data are as crucial to the success of computer vision projects as the algorithms themselves.
How much training data is required depends on the task you want the machine to accomplish. If you’re going to use CV to identify types of animals only, you will need considerably less training data than if your machine needs to recognise any image. The more objects you want your device to determine, the more samples it will need.
Everyday Uses of CV
So, we have a fundamental idea of Computer Vision and how a machine learns to see, but what are the everyday uses of CV?
If you are in a foreign country and confused by a sign, you no longer need to struggle with asking a passer-by who does not speak your language the meaning of the sign. All you need to do is point your phone’s camera at the sign, and using CV, Google Translate will give you the sign’s definition immediately.
If you wanted a picture of a “small brown dog wearing a red coat,” a search engine’s algorithm previously relied on the image’s metadata to return images in the not-so-distant past. Nowadays, search engines use Computer Vision to browse and retrieve accurate images based on their stored content rather than the provided metadata.
Computer Vision helps keep our roads and pavements safe by detecting defects early by monitoring changes in asphalt and concrete. This decreases of risk of road and pedestrian accidents.
Computer Vision for Businesses
Using AI for company activities is a time and money-saving method to manage a business. Artificial Intelligence, which includes Computer Vision, focuses on reducing human input by automating operations, maintaining a consistent level of efficiency and correctness to improve results and effectiveness.
No matter how careful and diligent an employee is, repetitive manual activities can easily lead to errors. Humans make mistakes, but machines do not. Detecting human error can be complicated, time-consuming, and expensive, but failure to do so can lead to losing customers or land you in court.
Using AI processes offers an automated approach for all kinds of businesses, decreasing human error, and increasing productivity and performance.
Let’s look at how some business sectors can benefit from AI.
In the real estate sector, agencies and portals use Computer Vision to match a buyer with the right property. A client can enjoy a real-time tour of a building. CV also allows a machine to give clients an estimated cost appraisal on accommodation. It computes value by the available space, the number of floors, the size of the rooms, and comparable properties in the area. In real estate, CV helps buyers or tenants find a home that offers the features they desire at the right price.
Computer Vision is expected to transform how we shop in the not-so-distant future. Waiting in long queues when grocery shopping is a pet hate for many, hence the popularity of online food and household goods shopping. But thanks to Computer Vision there will soon be no need to queue to pay for your items. It will be a case of visiting a shop, picking up what you need, and leaving. Computer Vision will handle the payment process, and because there is no room for human error, any offers and discounts will be correctly applied. The technology omits the worse part of grocery shopping, allowing you to go to your next destination in your self-drive car, sitting back and enjoying the view – also made possible by CV.
The hospitality sector is undoubtedly in need of rescuing, thanks to the impact of COVID-19. Considerable changes are needed for many businesses to survive, and only those who adapt are likely to weather the storm. Computer Vision could be a ray of hope for the struggling hotel and hospitality industry.
Computer Vision helps hospitality businesses provide a personalised service, for example, by identifying an important client on arrival. Staff are alerted and can offer an enhanced service. Humans are fallible when it comes to acknowledging important guests, as even the queen was once turned away from the Windsor Horse Show as the guard failed to recognize her and believed her to be a “random old dear”.
There is nothing guests appreciate more than an individual proactive service. This might not be possible in a coffee shop, but a luxury hotel can benefit greatly by using CV in this manner.
Face recognition is now a reasonably established CV technology. As well as recognising VIPs, it can help staff identify known troublemakers or criminals in nightclubs and hotels, improving guest and employee safety.
CV age recognition helps establishments control the sale of alcohol and tobacco to minors without asking for ID. This reduces the workload of personnel and allows them to focus on more income-generating tasks.
CV can also help staff with Covid protocols in crowded spaces. Not only does CV control reduce the risk of spreading the virus, but it also gives customers a sense of safety and well-being.
In service areas, Computer Vision can alert staff of unexpected increases in guests. CV can also collect data on patterns of guest movement inside premises to help management arrange for adequate staff for any given hour of the day.
Improving kitchen efficiency and reducing food waste is a recent use of CV that could transform food management and prevent unnecessary waste. It captures food wastage non-intrusively by using cameras placed over bins.
Food waste data is vital to help restaurants cut costs and reduce carbon emissions. Discovering exactly how much food is thrown out without humans estimating helps kitchen personal make informed choices when ordering.
CV overhead cameras can furthermore detect if a staff member is preparing food incorrectly. This is important, as when a customer orders his favourite meal, he expects to get the exact same plate of food each time. CV helps determine if different cooks are modifying, adding, or omitting components of any meal on the menu.
All sorts of businesses need security, from hotels to car parks to warehouses. Computer Vision has revolutionised surveillance as businesses no longer need to rely on human accuracy and a possible wandering attention span.
It is tedious for a human to constantly stare at a monitor to watch passing foot traffic or an empty corridor on a screen waiting for unusual activity. According to a 2016 study completed by Microsoft, a person’s attention span had dropped from 12 seconds in 2000 to 8 seconds in 2016, a figure that decreases every year. This data shows humans are easily distracted, which is not useful for security management.
With the introduction of innovative Computer Vision technology, machines can identify and analyse objects and send data to a cloud for further inspection. Be it crowd detection, face recognition, spotting a concealed firearm, or unusual behaviour detection, CV technology can notify staff of abnormal activity immediately.
Potential of CV in business
In business sectors where margins are tight, adopting AI and CV is a step in the right direction. Two years back, a McKinsey report on the global economy said that companies that ignore AI might see a significant drop in cash flow. Not using AI will affect businesses in different sectors to different degrees. Still, in most fields, vision AI has evolved to the stage that it can play a key role in business management and improve efficiency, customer experience and increase profit margins.