Video analysis with AI Vision and GPT

In today’s world, we need to analyze and consult countless documents, but the information we need to analyze or interpret is not always composed of text, the amount of audiovisual content generated and shared daily is overwhelming.

Companies from various sectors, from stores, journalists, businesses based on audiovisual content generation, to security companies with surveillance cameras, need advanced tools to analyze and extract relevant information from videos.

This is where Azure AI Vision combined with GPT comes into play, offering a powerful and complete solution that not only allows us to transcribe or extract insights from a video but the combination of these technologies provides more detailed and effective results.

In this article we will see different solutions that allow us to analyze videos as Azure Video Indexer, GPT with Azure AI Vision.

What is Azure Video Indexer?

Azure Video Indexer is a video analysis service based on artificial intelligence that allows us to analyze our videos and extract meaningful data such as: identify objects, transcribe dialogues, analyze sentiment, extract audio effects, keywords, topics or entities.

It provides an efficient way to convert unstructured content into structured and usable data.

Here is an example of the information it analyzes from a video of a motorist committing an infraction on the M30.

In today’s world, we need to analyze and consult countless documents, but the information we need to analyze or interpret is not always composed of text, the amount of audiovisual content generated and shared daily is overwhelming.

This service is very useful, but sometimes and in certain use cases the information provided may not be complete enough. In this article we will see how using AI Vision with GPT we will be able to perform a much more powerful analysis of our videos.

GPT4V and GPT-4o

Generative artificial intelligence allows us to call a single model to which we can ask an infinite number of requests such as translating, sentiment analysis, content writing, content classification among many other things with amazing results.

Thanks to the latest models, it not only receives text as input, but can also receive images as input, these are called multimodal models.

Within the available GPT models provided by the Azure OpenAI service we have two models that allow us to accept text and images as input, therefore, analyze images: GPT4V and GPT4o.

Why combine AI Vision with GPT?

Integrating AI Vision with GPT models mentioned above will allow us to obtain a video analysis tool that not only identifies elements and transcribes content, but also interprets and contextualizes the information.

With AI Vision we can analyze our videos and with GPT we will be able to interpret them.
This is especially useful for:

1. Contextual interpretation: GPT can understand the context and intent behind the dialogue and actions in a video, providing deeper and more meaningful analysis.
2. Insights generation: Unlike traditional analytics that only extract data, GPT can generate insights and recommendations based on the video content.
3. Task automation: From creating summaries to identifying key moments, this combination can automate many tasks that previously required human intervention.

In addition, this combination allows us to analyze our private videos and integrate the solution with our systems and developments, managing to synchronize the relevant business information extracted from the videos with our day-to-day tools.

Benefits of Using Computer Vision and GPT

1. Comprehensive and detailed analysis: The combination of Azure’s video analysis capabilities with GPT’s natural language understanding enables richer and more detailed analysis. Not only words and objects, but also contexts, emotions and tones can be detected.
2. Improved decision making: By providing deeper insights, companies can make more informed and strategic decisions based on their video content.
3. Time and resource savings: Automating the video analytics process significantly reduces the time and resources required to review and understand large volumes of audiovisual content.

Use Cases

1. Security and surveillance: In the security domain, this technology can help analyze surveillance video to detect suspicious behavior and improve incident response.
2. Retail and stores: Stores can analyze video from security cameras to better understand customer behavior, optimize store design and improve the customer experience.
3. Education: Educational institutions can use these tools to transcribe and analyze videos of lectures and classes, providing students with more accessible and personalized resources.

Conclusion

The integration of AI Vision with GPT represents a significant evolution in video analytics, enabling organizations to extract and use information more effectively. This winning duo offers a complete solution that not only analyzes, but also interprets and contextualizes, providing richer, more actionable results.

Companies in a variety of industries are already leveraging these technologies to transform their management of audiovisual content, and the potential continues to grow as both technologies continue to advance.

This article demonstrates how the combination of Azure AI Vision and GPT can revolutionize video analytics, providing an invaluable tool for companies and organizations in a variety of industries. If you are interested in exploring more about how these technologies can benefit your organization, feel free to contact us at Bravent.