How GenAI and Video Analytics Are Transforming Video Content

A football team has two of the biggest stars on the field, one a skilled playmaker and the other an unstoppable scorer (we won’t mention names, we’ll leave that to your preference). That’s the simple explanation for combining GenAI and Video Analytics. This technological duo is more powerful than ever, changing the world as we know it. When combined, they can turn any industry’s results upside down because together they equate to higher security and safety, more sales, better customer experiences, easier operations, and cost savings.

What is GenAI? Why Does It Matter for Video Analytics?

First, let’s get the facts straight: According to research by Precedence Research, the video analytics industry is expected to reach $94.56 billion by 2034 ($50.80 billion by 2032 – Fortune Business Insights), while the GenAI market is expected to reach $1.3 trillion by 2032 (Bloomberg Intelligence, 2023).

These huge numbers are not just a figment of the imagination; they reflect GenAI’s and Video Analytics’ importance.

Generative AI is a class of AI systems designed to create/produce/generate new content (text, images, audio, or other data types) in real time by understanding patterns and structures within pre-existing data and reproducing new content from it. The true power of video analytics lies in its ability to transform video big data content from inert recordings into powerful sources of information, insights, and conclusions, and then into decision-making.

A scene from the past: Security teams watch hours of surveillance footage searching for the cause of a problem (after the event has already occurred), a process that is not only time-consuming but also prone to errors and inconsistencies.

A scene from the present, not the future or science fiction: Leveraging advanced deep learning algorithms, generative AI (GenAI) video analytics can transform hours of footage into valuable, actionable insights in real time, even going so far as to understand context and make predictions.

How GenAI-Powered Video Analytics Works

Generative AI has made video analysis faster and smarter than ever, to the point where it no longer relies on humans for processes like monitoring, or, in other words, no longer requires human intervention.

Generative AI (such as ChatGPT, DeepSeek, and Gemini) is able to search video clips for specific segments, extract and summarize the most important information, and advanced versions can even analyze tone of voice and emotion.

The bottom line is that AI understands context, not just analyzes it, using techniques such as:

• Computer vision: to understand images and videos.
• Machine learning: to learn from data, understand context, improve itself, and generate various types of content (GenAI uses large language models, such as pre-trained generative transformers (GPT) and variational autoencoders (VAEs)).

Also you can learn more about: AI Cameras

How GenAI and Video Analytics Work Together

Let’s imagine a scenario: A retail project manager wants to analyze customer behavior in his retail stores, which are spread across Riyadh, the capital of Saudi Arabia. These are the (simplified) steps involved in the analysis:

• First, data preparation is performed by converting video content captured by surveillance cameras into formats suitable for AI processing.
• Second, features are extracted from the video, such as identifying important elements in each frame—people, objects, actions, and movements.
• Third, patterns are identified and how these elements relate to each other across frames.
• Fourth, a summary is generated using GenAI models.

This way, the business manager knows where to display his merchandise, the best and least attractive locations in the stores, when customers congregate, how to facilitate customer movement and increase customer satisfaction, and more.

Also you can learn more about: Video AI Analytics

Transforming Industries with GenAI and Video Analytics

The potential applications of GenAI and video analytics span virtually all sectors. Let’s review some of the most prominent ones:

Retail and Understanding Customer Behavior

By analyzing how customers move through stores, interact with products, and interact with displays, retailers can:

• Improve store layout
• Evaluate staff and increase satisfaction
• Distribute inventory
• Manage queues
• Reduced shoplifting
• Demographic analysis

Smart Cities and Transportation

GenAI-powered video analytics helps cities:

• Monitor traffic
• Predict congestion
• Identify incident-prone areas
• Optimize signal timing

Besides traffic, AI-powered video analytics systems enhance public safety by detecting loitering objects or individuals in restricted areas.

Security and Surveillance

Unlike passive traditional CCTV surveillance, which requires a human observer to detect problems, video surveillance systems powered by artificial intelligence offer the following advantages:

• Automatically detects unusual behavior
• Identification of unauthorized access
• Recognition of potential security threats

Facial and license plate recognition systems enable real-time identification of people and vehicles, enabling rapid response to incidents and more effective subsequent investigations.

AvidBeam: A Leader in Intelligent Video Analytics

AvidBeam was founded as an AI-powered video analytics company (built on years of experience by a group of highly skilled minds who worked at Intel). It developed technological solutions based on deep learning and big data processing techniques that enable real-time pattern and event recognition. The company offers integrated solutions, including:

1. AvidGuard: An intelligent surveillance system that detects intrusion, crowds, abandoned objects, and fires, with real-time alerting capabilities, contextual understanding and analysis, and even prediction.
2. AvidFace: An AI-powered facial recognition system (with over 90% accuracy). It is used for identity verification, access control (granting and denying access to specific locations), improving customer experience (in banks and hotels, for example), and law enforcement.
3. AvidAuto: A vehicle management system that recognizes license plates and tracks traffic, improving road and parking management.
4. AvidRetail: A customer behavior analysis tool for stores, providing data on visitor numbers, gender and age-group distribution, and interests, which helps improve marketing strategies.

The Future of GenAI in Video Analytics

The convergence of video analytics and generative AI is just beginning. As these technologies continue to evolve, we can expect:

• More sophisticated behavior prediction capabilities.
• Seamless integration with other systems, like access control and building management.
• Enhanced personalization in retail and entertainment.
• More nuanced emotional and contextual understanding.
• Greater privacy protection through advanced anonymization techniques.

Also you can learn more about: AI Video Analytics

All in All

GenAI-powered video analytics represents nothing less than a revolution in how we understand and interact with visual information. By transforming passive footage into actionable intelligence, GenAI and video analytics technologies help organizations make better decisions, enhance security, improve customer experiences, and operate more efficiently. At AvidBeam, we’re proud to be leading this transformation, developing solutions that harness the full potential of generative AI to decode the value hidden in video content.