ChatGPT Video Content Analysis: A New Frontier

In this post, we begin by examining the current limitations of existing customized ChatGPTs (or former ChatGPT plugins) for video content analysis. Traditional video content analysis tools often prioritize audio processing over visual elements, constraining the comprehensiveness of analytical capabilities.

Additionally, we'll explore how our proprietary custom video events detection technology developed at LettiNotes can effectively address this challenge. Spoiler alert: it can.

Lastly, we invite readers to nominate the most pertinent area of video analysis wherein our company would ideally develop custom ChatGPTs.

Problem: The Misconception

If we consider the general task of knowledge extraction from video, one prevailing approach entails converting a video's audio into a transcript and subsequently analyzing this transcription using tools like ChatGPT ( e.g. Review: Top 10 AI Video Summarizers: Time-Saving Solutions ). This method can be enhanced by conducting a basic analysis of the video frames themselves. Such an analysis may involve scene detection, the interpretation of charts and graphs visible within the frame, and the use of image recognition techniques to identify objects within the frame.

As a result, traditional video content analysis tools frequently heavily depend on audio processing while overshadowing the visual component. Although effective for certain insights, this method neglects the core aspects of video formatting, ultimately limiting the breadth and depth of analytical capabilities.

Our Solution: Context-Based Video Events Detection Technology

At our company, we are committed to revolutionizing video content analysis. Our approach prioritizes the visual aspect by detecting a custom set of key video events. In our approach, we shift the focus to analyzing the sequence of video frames, detecting ongoing events, and understanding the context of what is happening.

According to our approach, customizing a basic set of video events, for example, for construction site, may look like this:

The result of this video analysis is a list of timestamped video events. This list can then be further processed. For example, the statistics of these events can be visualized with various types of charts using our software, or these events can be processed using methods such as ChatGPT.

We are confident that this innovative strategy allows for a comprehensive and detailed understanding of the video content, unlocking richer insights and a deeper understanding of visual data.

Call to Action: Select Video Content Topics

We invite you to help us shape the future of video content analysis. Select video topics for which you believe our approach could revolutionize the insights gained. Whether it's educational content, surveillance video, sports, or online tutorials, we are eager to develop tailored ChatGPTs that harness the potential of our video event-based approach, delivering a more comprehensive and insightful video analytics experience.

Together, let's redefine the parameters of visual intelligence and unlock unparalleled analytical possibilities.