Top Business Use Cases of Artificial Intelligence and Computer Vision in Retail, Automobiles and More...

Computer vision, an AI technology that allows computers to understand and label images, is now used in convenience stores, driverless car testing, daily medical diagnostics, and in monitoring the health of crops and livestock.

From our research, we have seen that computers a proficient at recognizing images. Today, top technology companies such as Amazon, Google, Microsoft, and Facebook are investing billions of dollars in computer vision research and product development.

This post explores what kind of uses of computer vision technology are currently popular across various industries including Retail and Retail Security, Automotive, Healthcare, Agriculture, Banking, Industrial.

Computer Vision in Retail and Retail Security

1. Amazon

Perhaps the most commonly known use of this technology, Amazon recently opened to the public the Amazon Go store where shoppers need not wait in line at the checkout counter to pay for their purchases. Located in Seattle, Washington, the Go store is fitted with cameras specialized in computer vision. It initially only allowed Amazon employee shoppers but welcomed the public beginning in early 2018.

The technology that runs behind the Go store is called Just Walk Out. As shown in this one-minute video, shoppers activate the IOS or Android mobile phone app before entering the gates of the store.

Cameras are placed in the ceiling above the aisles and on shelves, Using computer vision technology, the company claims that these cameras have the capability to determine when an object is taken from a shelf and who has taken it. If an item is returned to the shelf, the system is also able to remove that item from a customer’s virtual basket. The network of cameras allows the app to track people in the store at all times, ensuring it bills the right items to the right shopper when they walk out, without having to use facial recognition.

As the name suggests, shoppers are free to walk out of the store once they have their products. The app will then send them an online receipt and charge the cost of the products to their Amazon account.

In retail fashion, Amazon has applied for a patent for a virtual mirror. In the patent, the company said, “For entertainment purposes, unique visual displays can enhance the experiences of users.”

The virtual mirror technology, sketched in the patent image below, is described as a blended-reality display that puts a shopper’s images into an augmented scene and puts the individual in a virtual dress.

According to the patent, the virtual mirror will use enhanced facial detection, a subset of computer vision, whose algorithms will locate the eyes. Catching the user’s eye position will let the system know what objects the user is seeing in the mirror. The algorithms will then use this data to control the projectors.

Amazon has not made any announcement on this development and the virtual mirror has not been deployed, but the sketches released by the patent office show how a user could see illuminated objects reflected on the mirror combined with images transmitted from the display device to create a scene.

Amazon has previously released Echo Look, a voice-activated camera that takes pictures and six-second videos of an individual’s wardrobe and recommends combinations of outfits.

This 2-minute review of the app shows how it claims to use Amazon’s virtual assistant Alexa to help users compile images of clothes and can even recommend which outfit looks better on the individual.

As the video shows, a user can speak to the gadget and instruct it to take full-body photos or a six-second video. The content is collated to create an inventory of the user’s wardrobe, according to Amazon. Alexa compares two photos of the user in different outfits and recommends which looks better.

2. StopLift

In retail security specific to groceries, Massachusetts-based StopLift claims to have developed a computer-vision system that could reduce theft and other losses at store chains. The company’s product, called ScanItAll, is a system that detects checkout errors or cashiers who avoid scanning, also called “sweethearting.” Sweethearting is the cashier’s act of fake scanning a product at the checkout in collusion with a customer who could be a friend, family or fellow employee.

ScanItAll’s computer vision technology works with the grocery store’s existing ceiling-installed video cameras and point-of-sale (POS) systems. Through the camera, the software “watches” the cashier scan all products at the checkout counter. Any product that is not scanned at the POS is labelled as a “loss” by the software. After being notified of the loss, the company says it is up to management to take the next step to accost the staff and take measures to prevent similar incidents from happening in the future.

The three-minute video below shows how the ScanItAll detects the many ways items are skipped at checkout, such as pass around, random weight abuse, cover-up, among others, and how grocery owners can potentially stop the behaviour.

Based on news stories, the company claims to have the technology installed in some supermarkets in Rhode Island, Massachusetts, and Australia.

Computer Vision in the Automotive Industry

According to the World Health Organization, more than 1.25 million people die each year as a result of traffic incidents. The WHO adds that this trend is predicted to become the seventh leading cause of death by 2030 if no sustained action is taken. Nearly half of the road casualties are “vulnerable road users:” pedestrians, cyclists and motorcyclists. According to this research, there’s a clear theme to the vast majority of these incidents: human error and inattention.

1. Waymo

One company that claims to make driving safer is Waymo. Formerly known as the Google self-driving car project, Waymo is working to improve transportation for people, building on the self-driving car and sensor technology developed in Google Labs.

Waymo 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. The company also reports that the software has been tested on 7+ million miles of public roads to train its vehicles to navigate safely through daily traffic.

The 3-minute video below shows how the Waymo car navigates through the streets autonomously.

According to the video, 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 manoeuvre through different situations such as construction sites, give way to emergency vehicles, make room to cars that are parking, and stop for crossing pedestrians.

This post first appeared on Pegasus One blog. Please click here to read the complete article.