At the turn of the 20th century, computer vision seemed little more than a crazy unrealistic dream of scientists and scholars. The Summer Vision Project was perhaps the first computer vision project that was assigned to undergrads back in 1960. The key vision then was to utilize the computing power (whatever existed then) to develop a computer program (algorithm) capable of understanding, analyzing, interpreting, and responding to stimuli from the surrounding.
Since then there have been growing efforts to develop more robust and intelligent computer vision algorithms that are able to understand, interpret, and interact with the surrounding. The fast-track technological advancement in the 1990s that significantly reduced the prices and increased availability of high-powered supercomputers further increased the development of computer vision technology as engineers rushed to come up with more complex and robust mathematical models.
Today, with decades of research and refinement, computer vision technology has greatly matured and very much a reality.
But what exactly computer vision technology is all about?
Start Gowing with Folio3 AI Today
We are the Pioneers in the Computer Vision – Do you want to become a pioneer yourself ?
What Is Computer Vision Technology For SMEs and Enterprises?
To put it simply, computer vision is a subfield of Artificial Intelligence that is meant to take understand the visual components (imagery or video) for identification, analysis, processing, and extraction of information. Itâs the technology that fuels the limitless application of image processing software, image segmentation overcoming the inherent limitation of the human eye to process the information from visual components.
Today, computer vision technology is able to train models for effective and efficient analysis of the visual components (imagery and videos) to yield discreet information which otherwise isnât possible for humans to do it on their own.
Computer vision has remained an area of study as a machine learning concept for quite some time. As far back as the 1950s, the raw concepts of computer vision were used to analyze environmental objects and systems. Although still in its infancy then, the core concept for the technology has remained consistent â devising useful information from the visual components using intelligent machine learning models that are able to identify, analyze and process information from visual components. However, the technological restrictions of that time-restricted the scope and application of computer vision technology back until the 1990s, when finally supercomputers were started to mass produce and be available for scientists to continue their research for the development of robust computer vision technology.
Today, the technology has matured greatly with advanced algorithms being developed for practical utilization of the technology in daily lives, which have proved to be of great worth for personal and commercial use. Today, various companies are developing comprehensive and advance computer vision technology applications with cross-industry utility.
Read our detailed guide on how does computer vision works?
Applications of Computer Vision Technology
Computer vision technology is making its way into all aspects of commercial and personal lives. Today, nearly all industry sectors private and public included are utilizing the power of computer vision technology to track, process, and interpret the world around them. Below we have come up with some of the top applications of computer vision technology;
Improved Online Merchandising
For the past two decades, online merchandising has solely relied on tags to understand customersâ search queries. For instance, to define a bag, an online merchandiser attach various tags with the products like âbagâ, âPolyesterâ, âBlackâ, âcottonâ or other tags that enable to refine the search results for the users.
The system has been working fine for online merchandising for decades, even though this wasnât the most efficient or effective system. Nonetheless, with the rapid adoption of computer vision technology, this is soon going to change, making it must easier for customers to find the precise merchandise they are looking for.
The technology will essentially eliminate the reliance on tags for merchandise search, rather it will bring into place comparison for actual physical characteristics of products in the image. In simple terms, in the future, customers no longer would have to rely on tags to find out the best product, rather they will be able to perform image similarity to find the exact product (size, shape, color, and other physical characteristics) they are looking for.
Redefining the retail experience
Perhaps the most fascinating and exciting application of computer vision technology is its ability to redefine the retail experience for customers. Amazon Go is a prime example of the capacity and capability of computer vision technology for users.
If you already arenât aware of the Amazon Go stores and image analytics, there are physical stores with no checkout lines. Customers can visit the stores with no cashiers. You can just pick up whatever you want and leave the store. The store is fitted with a camera system all across, which is able to track and identify the movements of shoppers. The smart cart carried by customers also comes with scanners, which instantly detect any items that are placed or removed from the cart. The powerful computer vision algorithms running the cameras automatically detect and make transactions for the items from customersâ online account, thereby, saving them the hassle of going through the cashier lines.
Start Gowing with Folio3 AI Today.
We are the Pioneers in the Cognitive Arena – Do you want to become a pioneer yourself ? Get In Touch
Please feel free to reach out to us, if you have any questions. In case you need any help with development, installation, integration, up-gradation and customization of your Business Solutions. We have expertise in Deep learning, Computer Vision, Predictive learning, CNN, HOG and NLP.
Connect with us for more information at [email protected]
