21 Aug, 2019
Artificial intelligence (AI) is becoming more of a reality in today’s world. Computers can incorporate AI into their systems to be able to “see” what is happening around them and the world.
Artificial Intelligence, in simple term, is computer systems that can mimic human intelligence to make decisions and perform tasks such as speech recognition, language translations, and visual perception. With this in mind, computer vision (CV) can use AI to help “see” and understand the content of digital images. Computer vision processes these images and analyzes them at an in-depth level for decision-making.
According to Prof. Fei-Fei Li, computer vision is “a subset of mainstream artificial intelligence that deals with the science of making computers or machines visually enabled.”
Computer vision and Ai are modeled to assist humans, not replace them. They have already made its way in industries and businesses.
What they have been used for:
Employee tracking has typically been tedious and time-consuming when calculating a worker’s attendance, while also relying on them to be focused on the job. Many forms have been established to use in attendance besides the traditional form of hand-written attendance. Companies have used fingerprint, facial and card-based systems for automatically recording the hours an employee works.
When the workers enter the workplace, it is quite difficult for an administrator to monitor every employee. They cannot be guaranteed that each of the employees is doing what they need to do.
With computer vision and AI, it resolves these issues. These systems can record the employee’s attendance by facial recognition and can record the time an employee spends in their workstation.
With auto attendance, real-time face recognition is used when an individual enters a workplace. AI is on-site to allow them in or to analyze which employee has entered. After they come in, monitoring is continued.
Trebeya, a data analytics and artificial intelligence company, used a computer vision to monitor an area in their workspace. In the video, it captured the detection of objects and people, where they were or where they were going to. With this example, it becomes possible to track an individual’s movement over some time across multiple screens as well as notice posture or even monitor emotion.
Computer vision is making its way into almost every major industry, and retail and restaurants are no exception.
In retail and restaurant industries, utilizing computer vision solutions is a critical component for an absolute store experience customer search for. From the moment they pull into the parking lot, certain steps are taken to give them the best and smoothest experience.
Once the customers are in the parking lot, CV can identify them by their license plate number along with facial recognition to confirm their identity. This occurs when they leave their vehicle as they enter the store.
With this, retailers and restaurant workers can bring out their orders to them as soon as they park their cars. Associates would be able to welcome members or VIP customers by clientele recognition tablets without them having to announce themselves.
Along with instantly recognizing customers, computer vision technology can eliminate scanning items on barcodes and checking out will be the thing of the past.
Amazon Go concept gives a checkout-free retail experience. It tracks shoppers using CV by sensors on the shelf when an item is picked up. The items they chose will be registered to their Go mobile app which removes the checkout process completely. When the customers leave the store, the Go app will automatically remove their money from the shoppers’ card that is processed in the app.
AI in restaurants have become more appealing in the foodservice industry, with restaurant employee turnover rates regularly over 70 percent and an ongoing effort for recruiting and keeping employees, AI can solve some of these problems.
Robots, delivery bots, and chatbots are the main objectives restaurants focus on AI integration. A few industries have already or tested AI and robots. Dominos delivered a pizza with a drone, KFC is surveying face-recognition technology to help create a personalized customer experience, and a burger-flipping robot was made, but has since “retired.”
Automated scene analysis techniques have been a topic of attention in computer vision. By using computer vision in events with large crowds, it can model and recognize human activities and interactions.
The application of these techniques is usually in simple environments but modeling larger groups of people and crowds have been attempted a few times now. Crowd analysis and behavior have become a main interest in the surveillance domain.
CV monitors the area for visual surveillance crowd management and public space design.
The features of CV are equipped into the cameras at the event or tradeshow. It uses algorithms to track, recognize, and understand the different items in the video surveillance. By using facial recognition, it can follow anybody and measure how long they stay in an area or how often they move around.
Computer vision uses various methods to produce informed decisions based on obtaining, processing, analyzing, and comprehending digital images. They are used in many functions in various industries and the effects of these advancements are astounding.
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