Visionary Disruption: High-level Insights with Azure Video Indexer & GPT-4 Turbo with Vision

Figure 1 Generated with Azure OpenAI Dall-E 3Figure 1 Generated with Azure OpenAI Dall-E 3

Video analysis combined with cutting-edge natural language processing (NLP) technologies have created new opportunities for innovation in today's fast-changing digital environment. Here are some ideas for impactful integration between Azure AI Video Indexer (VI) and GPT-4 Turbo with Vision. These suggestions are aimed at enhancing video analysis capabilities with the power of Large Language Models. They enable business value distillation from video content, offering insights and opportunities through ad-hoc chat interface for content discovery or automated custom tasks. Here are some compelling use cases demonstrating this potential for a variety of industries.

Educational Copilot with VI and Azure OpenAI GPT-4 Turbo with Vision

The Educational Copilot with VI and GPT-4 Turbo with Vision integration revolutionizes the way recorded lectures, such as massive open online courses (MOOCs) or TED talks, are analyzed and utilized. Azure Video Indexer, with its advanced video analysis capabilities, can identify topics, named entities, and sentiments within the videos. Using GPT's deep understanding of natural language and visual information, educators and students can get detailed analyses and summaries of lectures, a more engaging and personalized learning experience. By grounding analysis with Retrieval-Augmented Generation (RAG), users can explore topics in depth, enabling a more comprehensive understanding of the subject matter. For this purpose, we developed the PromptContent feature into VI which turns indexed videos into semantically segmented video prompts per video scene. By leveraging vector DB services like Azure Search, VI grounds video archives for retrieval and RAG tasks. See more details in this blog post.

For example, a university for instance can use PromptContent RAG grounding and GPT-4 Turbo with Vision capabilities to answer complex questions that span across multiple video lectures, such as “How does quantum cryptography relate to information theory?” or “What are the ethical implications of gene editing?“. By using VI to extract relevant video segments based on keywords and entities, and GPT-4 Turbo with Vision to generate natural language summaries and explanations, students can access concise and accurate information that enhances their learning outcomes. Additionally, educators can use this integration to create interactive quizzes and assessments that test students' comprehension and critical thinking skills, as well as provide personalized feedback and guidance.

We recently published a paper that describes a video retrieval user experience over video archives – “VCR: Video representation for Contextual Retrieval”. Semantic search was found to be significantly improved when it grounded LLMs to the archive using multimodal insight. The search experience presented in this paper leverages GPT-4 to augment user queries and embed them using Azure OpenAI Embedding ADA-002.

Public Safety & Justice

Our integration offers innovative solutions for enhancing security and law enforcement operations. By utilizing VI's capabilities to detect specific objects, such as weapons in CCTV footage, and cropping the relevant images, GPT-4 Turbo with Vision can classify whether the individuals in the footage are law enforcement personnel. This advanced recognition and classification system can significantly augment security measures, offering rapid and accurate assessments that are crucial for maintaining public safety.

Protecting Privacy with

The integration between VI and GPT-4 Turbo with Vision can help protect the privacy of individuals who are captured by police body cameras. By using VI's face detection, recognition, and redaction technology, the system can automatically identify and blur or redact the faces of bystanders, witnesses, or victims who are not involved in the police operation. GPT-4 Turbo with Vision is used here to classify other officers appearing in the footage through their uniform. This way, the system can preserve the privacy and anonymity of these individuals, while still allowing the police to review the footage for evidence or accountability purposes. This privacy-preserving system can also reduce the labor, time and costs associated with editing the footage, as well as minimize potential complaints from the public. As such footage could also be harmful, automating these manual workloads cancels out its impact. This application idea demonstrates how can enhance the ethical and responsible use of police body cameras, while also improving the efficiency and transparency of law enforcement.

Revolutionizing Marketing with AI

VI and GPT-4 Turbo with Vision together create a transformative approach to automated marketing strategies. By detecting textual logos in TV shows and other video content you can understand whether the brand is portrayed in a positive light or if the context discourages its use. Such insights are invaluable for assessing brand visibility and sentiment, enabling marketers to tailor their strategies more effectively. There are many examples of misfortune marketing events, here is one inglorious moment by, well…, Microsoft. The figure below demonstrates this general capability using ChatGPT on a sampled key frame by VI.

Figure 2 Blue screen incident at the Windows 98 presentation.Figure 2 Blue screen incident at the Windows 98 presentation.

Personalizing Retail Experiences

One promising application is to personalize the retail experiences of customers visiting physical stores. By using VI's people tracker to detect customers and distinguish them from employees, GPT-4 Turbo with Vision can then generate personalized recommendations based on their visual appearance, preferences, purchase history, and current location within the store. These recommendations can be delivered through digital displays, mobile apps, or smart devices, enhancing customer engagement. This system can also provide useful feedback for the store managers, such as which products are often checked but aren't converted, which sections are most visited, and optimize the store layout and inventory accordingly. This personalization system can potentially boost sales while also creating a more enjoyable shopping experience for customers.

For example, let's consider Kemba – Tal's pet. When she walks with Kemba into a pet shop, personalized products targeted for a Border Collie could be presented to Tal by leveraging VI's detection and tracking, face detection and GPT-4 Turbo with Vision integration. Targeted products could focus on Kemba's size, diet, etc.

Figure 3 KembaFigure 3 Kemba

Enhancing employee safety in Manufacturing Operations

Ensuring compliance with safety regulations and company policies is paramount. Through this integration, companies can employ VI to detect employees within video feeds, using custom face ID technologies. GPT-4 Turbo with Vision can then assess whether these individuals are adhering to company uniform codes, including the proper wearing of helmets and other safety gear. This automated compliance monitoring streamlines the enforcement of company policies through safety regulations.

Conclusion

Integrating Azure Video Indexer and GPT-4 Turbo with Vision can present a significant leap forward in video content analysis, from enhancing educational content with in-depth analyses to improving public safety, revolutionizing marketing strategies, and ensuring compliance in manufacturing. Such integrations may harness the latest Vision-Language models to solving real-world challenges, providing you with innovative solutions to drive success in the digital era.

Explore Azure AI Video Indexer Today

 

This article was originally published by Microsoft's AI - Machine Learning Blog. You can find the original article here.