Fascinating Examples of Computer Vision in Advertising

Computer Vision is a new technology that exploits the power of artificial intelligence to analyze images. In advertising, it has been attributed to identifying people, cars, and many more objects in a scene or advertisement. A new world of advertising lies ahead. It has enabled the next generation of intelligent products that communicate with users through unobtrusive and intuitive interactions. This blog describes how computer vision connects advertising to consumers in new ways that enhance the overall experience. It explains how computer vision technologies are integrated into products and used to analyze consumers' behaviors.

According to a new report by Reports and Data, the Global Computer Vision System Market has been forecasted to reach USD 25.69 Billion by 2028.

Social Media Marketing

More than 2.32 billion people worldwide use social media to keep in touch with friends, share ideas and express their views. This represents more than a third of the total number of Internet users in 2016, according to eMarketer.

Computer Vision can be applied not only for the general aim of monitoring all activities on the social media pages but also for specific objectives, including user analysis. Computer Vision solutions can be customized to fit different aspects of social media. It has the potential to provide real-time information to marketers that are directly related to consumer behavior.?

Computer vision has made social media possible to track behavior in real-time through digital analysis, creating powerful measurement capabilities for business owners. This technology allows the tracking of user interactions with videos, images, and audio content, providing marketers with valuable information that can help them grow their target audience.

For example, Facebook uses a technology called a DINO to train vision transformers (Vit). Without any supervision, this model can detect and classify objects in a video and image. In addition, they categorized things to aid in task assignment, such as changing the background of a video.

Virtual Assistant

When it comes to marketing, one size does not fit all consumers. Some shoppers need assistance from a virtual assistant to look for products that will suit their needs, while others don't need any help to find what they want. For example, if you're looking for a unique gift for your wife, you're probably willing to spend hours going from store to store and compare prices and styles. If you have a deadline for buying a graduation gift, on the other hand, you might rely on a virtual assistant to get the best possible price within a specific time frame."

For example, Sephora Virtual Artist has taken this trend to the next level with their Virtual Artist. Virtual Artist allows users to upload a picture of their face, virtually try on different makeup products, and see how they would look without having to don't any makeup personally.?

Source: Sephora App

It uses an algorithm to recognize peoples' faces, determine their gender and age, and then match the customer to the perfect lipstick. It then creates a 3D avatar of the person's lips wearing this shade, lip liner, and lipstick. Next, the customer takes a selfie with their webcam. Finally, the software matches their photo to one of the customers' existing photos or avatar photos. Having done so, it makes thousands of tiny adjustments to elongate or shorten different parts of lips, change the size ratio between lips and nose, even tune the opacity of lipstick, etc.

Verified market research says Intelligent Virtual Assistant Market size was valued at USD 5.0 Billion in 2020 and is projected to reach USD 50.9 Billion by 2028.

Ad Targeting

Credits:?Advertima

Today there is a lot of ad targeting based on text and images on websites. You can look almost anywhere and see ads whose content is specific to the website you happen to be viewing and even your interests and beliefs. How does it work? The process involves extracting textual and visual information from web pages and using computer vision techniques to recognize the presence of products, movie titles, celebrities, logos, other images, etc. Facebook, Google, and most other ad serving companies use 'Computer Vision Targeting' to serve their ads.

For example, Facebook's AI research team has developed a tool to recognize photographs' faces, objects, and themes. It's a helpful tool that allows businesses to obtain essential information such as client preferences, interests, and demographics. The same technique is used to create a precise image of a brand loyalist and which products they appear to cherish the most.

Emotional Analytics

Emotional analytics is a field within the emerging discipline of computational psychology where computer vision technology is used to measure facial micro-expressions to improve target marketing. Emotions have been shown to have a profound impact on consumer behavior.

Emotional analytics is the application of computer vision techniques to achieve affect-aware computing. Affect-aware computing enables computers to automatically detect, analyze, understand and respond to human emotions through specialized hardware, software algorithms for perception-recognition, and intelligent data management and mining.?

Affect-aware computing scales up and automates the use of traditional market research techniques, such as focus groups and one-on-one interviews, by allowing algorithms to process vast amounts of data created from social media interactions, video-based marketing campaigns, and other sources, providing actionable insights that will help companies increase consumer satisfaction and loyalty.

For example, Unruly has partnered with a university in Kent, Moodagent, Affectiva, and Nielsen, to bring emotional intelligence to digital advertising. It's a brand-new tool that incorporates biometric, emotional, auditory, and neurological tests. This will help advertisers to maximize the emotional and commercial effects of their advertisements. And, also make sure that the commercials are in line with the brand's ideals.?

Source: The conversation

Placing Relevant Ads

The objective of Relevant Ads is to improve the relevance of the advertisements that you as a user will see and contribute to a more equitable internet environment for advertisers and publishers.

Computer Vision supports advertising in a variety of ways. It begins by scanning a page that contains all relevant data, such as images, videos, and data. Next, data and ads evaluate the context for communicating and understanding, what the page is about, and what a user expects from a page. Finally, computer vision selects the most relevant ad and integrates it with web page content, similar to how the ad placement would be positioned, to attract the maximum user attention. As a result, such a form of advertisement will pique the user's curiosity. This type of advertising is possible since machines can identify what an image looks like and what it includes.

For example, a machine can now distinguish between a "German Shepherd breed" and a "dog." With the advancement of technology, in-image ad insertion appears to be on its way to becoming the norm.

Credits: criteo

Conclusion

Computer Vision Technologies has been applied to various applications such as brand monitoring, detecting the brand logo and product labels, etc. In addition, it provides a new channel for advertisers to explore and engage with their customers through innovative strategies and techniques to enhance contact with potential consumers further. As a result, the technology can save companies billions in costs and give advertisers better results.

With expertise in computer vision, Visionify is highly capable of delivering custom computer vision solutions. We also design and implement novel algorithms for real-time tracking, object detection, and recognition, etc. Get in touch with us to get a live demo.