The Alchemy of Computer Vision in AI: A Promise

“If we want machines to think, we need to teach them to see”                                                                                                                          – Fei Fei Li  

The fantasy of a machine capable of simulating human vision is no longer a fantasy. Praise be to the flattering advances in Artificial Intelligence, innovations in Deep Learning and Neural Networks, computer vision has emerged as an overriding force in the subfields of Artificial Intelligence and Machine Learning by leaps and bounds in recent years. 

The plenty of exciting technological advances occurring in computer vision, a hotcake in the subset of AI Solutions, is the latest rage in town. Computer vision focuses on replicating and interpreting the complexity of human vision, making sense of the world with a sense of sight using computers to identify and process objects in images and videos akin to the human visual system. Confirming the market research and reports, the computer vision market was valued at US$ 4,643.3 million in 2019, is projected to reach US$ 95,080.5 million by 2027. In years to come, computer vision will undisputedly outdo humans in almost all varieties of tasks, bridging the gap between the digital and the physical world. 

Let us scoop out some of the most important areas shining in the glory of computer visions’ intelligent automation capabilities.

Autonomous Vehicles: 

Happening is the era of advanced, next-gen computer vision enabled autonomous cars. Imagine getting into your car, typing, or better, speaking a location into your vehicle’s interface, then letting it drive you to your destination hassle-free while you read a book, surf the web, or take a nap. Can anything get better than this? Absolutely not!. Self-driving vehicles, the stuff of science fiction since the first roads were paved are now possible with the advancements in computer vision techniques.

Computer vision is absolutely slaying in the domain of autonomous vehicles, assisting vehicles to perceive and understand the environment around them, perfecting them to operate correctly, using multiple cameras to gather a better picture of the environment around the vehicle than any normal driver, ruling out all possible human errors. The AI-based computer vision system can detect numerous items, inclusive of pedestrians, traffic signals, road signs, and more. They can also help the vehicles to maneuver through different situations such as construction sites, give way to emergency vehicles, make room for cars that are parking, and stop for crossing pedestrians.

According to the World Health Organization, more than 1.25 million people die each year in various traffic-related accidents mostly due to human negligence and inattention. With no human errors, distractions, and carelessness, autonomous vehicles can drastically bring down the number of road accidents by classifying and detecting objects, gathering large sets of data using cameras and sensors including location information, traffic conditions, road maintenance, crowded areas, detecting low light conditions and far more.

Facial recognition:

One of the most common applications of computer vision is facial recognition, beyond just unlocking phones or laptops, the biometric software behind facial recognition applications can accurately identify faces, better than people. The slew of opportunities offered by computer vision to identify unauthorized access to locations where non-authorized people shouldn’t make it extremely useful for the security sector. The ability of machines to accurately recognize individuals marks its effective service in the unmanned, automated immigration clearance gates to detect and thwart border crossings from known criminals and persons of interest, through facial recognition.

Healthcare:

The pandemic slammed the breaks on our healthcare system drawing more attention and attentiveness into the field of healthcare for accurate and faster detection of illnesses. Computer vision is the latest miracle drug that can accurately classify conditions of illnesses, reduce or eliminate inaccurate diagnoses and incorrect treatment, surgery simulation and surgical assistance, minimize false positives, detect early symptoms with high certainty and provide better treatment options for patients potentially saving their lives. Computer vision techniques collectively with Artificial Intelligence assist to automate numerous jobs like detecting cancerous moles withinside the photos of skin, reducing the amount of redundant surgical procedures, fruitless expensive therapies, faster lab results, and accurate measurement tools.

Computer vision will unquestionably revolutionize the future of imaging analysis, facilitating MRI and X-ray scans with interactive 3d imaging providing medical professionals a clear and better understanding of the patients’ health condition for a better and accurate diagnosis. The Healthcare industry is wholeheartedly adopting the technology of computer vision into the wide spectrum of medical procedures and also into the plethora of non-treatment applications ranging from patient monitoring, monitoring the progress of treatments, confirming patient identity, automatic operating room, electronic logs, patient identification during intake and course of treatment, keeping track of the patients and procedures, etc. 

The latest in Computer Vision enabled healthcare is smart glasses that can provide blind people an idea of the environment around them, helping them to identify obstacles, read traffic signs, shop names, guide them to the required designation, etc. Computer vision has made a successful impact in all lines of healthcare and has unleashed its full potential delivering life-saving functionalities for patients raising the levels of awareness and precision. 

Industrial:

Smart machines that can see, communicate and do the same work as humans with greater precision and better results are a compelling necessity of the current times. Computer vision applications can monitor the status of critical infrastructures, such as remote wells, industrial facilities, work activity, and site security, assisting humans in complex processes, saving time, and opening opportunities. These computer vision-enabled monitoring systems can act as tools for detailed positioning on the product lines- vision-guided robot, packing, inspection of barcodes and label scanning, labeling, tracking and tracing, defect reduction, anomaly detection, fault detection and evaluation of severity of the faults, saving the time taken for manually studying these faults. The online visual monitoring system has also reduced the site visits and its equivalent costs, which is an acute need in these pandemic times where it is difficult to visit sites on a regular basis laying impetus on machines minimizing human effort and interactions. 

Banking:

Computer vision technology has got the hearts of the banking industry as well, offering a provision of technologies providing image recognition applications that use machine learning to classify, extract data, and authenticate documents such as passports, ID cards, driver’s licenses, and checks. The most common application of AI in banking involves fraud detection and natural language processing, verifying the authenticity of customer ID or a paper check using their photographs captured through mobile devices. Certainly, AI will continue its emphatic journey in the financial services industry and proliferate in many good years to come.

Agriculture:

Computer vision did not miss the beat in agriculture, farmers have begun to adopt computer vision technology to improve their productivity. Computer vision-equipped drones with sensors, processors, storage devices, artificial intelligence analytics software, and other user interfaces capture images of the fields, measure and monitor the condition of crops giving indications on pest infestations, nutrient deficiencies, dehydration, and other metrics to estimate potential yield of harvest helping farmers to make informed decisions related to their lands, for more efficient growing methods to increase yields, and eventually increase the profit.

Retail and Retail Security:

The latest in vogue is the AI-enhanced retail stores, and Amazon let the rage on by recently opening to the public Amazon Go, where shoppers need not wait in line at the checkout counter to pay for their purchases. The cameras, coupled with computer vision technology can determine when an object is taken from a shelf and who has taken it. The system is also able to remove an item from the customer’s virtual basket if an item is returned back to the shelf. The network of cameras allows the app to track people in the store at all times, ensuring the billing of 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, an online receipt and charge for the cost of the products will be added to the buyer’s Amazon account.

In ensuring 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, 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. Using algorithms, Stoplift claims that ScanItAll can identify sweethearting behaviors such as covering the barcode, stacking items on top of one another, skipping the scanner, and directly bagging the merchandise.

Retailers across the world are exploring the efficacy of computer vision for a frictionless and mindful business space eliminating inefficiencies, losses, and theft, and it is predicted to only spike in the foreseeable future. 

Computer vision has absolutely crushed the AI market space, and its unbridled ecstasy will take down the skies in the coming years.

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