AI-DRIVEN VIDEO CONTENT ANALYSIS AND CATEGORIZATION

Abstract

The invention relates to an AI-driven system and method for automated video content analysis and categorization. Utilizing advanced machine learning and deep learning techniques, the system analyzes video data by extracting visual, audio, and contextual features to categorize content accurately and efficiently. The system can recognize objects, actions, speech, and events, enabling applications in areas such as content moderation, video summarization, and targeted advertising. It offers scalable, real-time processing, reducing the need for manual intervention while improving the speed and accuracy of video categorization across a wide range of industries.

Specification

Description:The present invention relates to the field of artificial intelligence and machine learning, specifically in the area of video content analysis and categorization. More particularly, it pertains to systems and methods that employ AI techniques, including machine learning, deep learning, and natural language processing, to analyze and categorize video content in an automated and scalable manner. The invention is applicable in various industries, including content management, social media, entertainment, advertising, and digital security, where large-scale video data needs to be organized and understood efficiently.
BACKGROUND OF THE INVENTION
The following description of related art is intended to provide background information pertaining to the field of the disclosure. This section may include certain aspects of the art that may be related to various features of the present disclosure. However, it should be appreciated that this section be used only to enhance the understanding of the reader with respect to th , Claims:1. A system for AI-driven video content analysis and categorization, comprising:
• A video input module configured to receive raw video data;
• A preprocessing module configured to extract frames, audio, and metadata from the video;
• An AI analysis engine, utilizing machine learning models to analyze the video content, wherein the AI analysis engine identifies and classifies objects, actions, and contextual features from the video;
• A categorization module configured to categorize the video into one or more predefined categories based on the AI analysis;
• A user interface for allowing a user to interact with the categorization process.

2. The system of claim 1, wherein the AI analysis engine uses convolutional neural networks (CNNs) for object recognition and classification within video frames.

3. The system of claim 1, wherein the AI analysis engine uses recurrent neural networks (RNNs) for action recognition and event detection within video sequences.

4. The system of claim 1, wherein the AI analysis

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