User-described Video Streams

Smart overview of the Invention

A method and system have been developed to create user-defined video streams within a virtual environment. This process begins by obtaining a representation of an object and interpreting a natural language description provided by the user. A trained neural network is utilized to generate a video stream that incorporates the specified object into the virtual environment described by the user. Users can further modify their virtual settings, prompting the system to produce updated video streams based on their requests.

Field of Application

The technology is primarily focused on video recognition and artificial intelligence, specifically for identifying objects in video streams. It aims to enhance user interaction through improved interfaces that integrate seamlessly with video content, enabling features like augmented reality interactions. This innovation addresses the challenges of recognizing and retaining information about objects in various video contexts.

Background Context

Video content is ubiquitous in daily life, spanning entertainment, education, and communication. However, viewers often struggle to retain information from videos due to the rapid pace at which visual and audio data is presented. Important objects may go unrecognized or overlooked, making it difficult for users to gather relevant information from the content they consume.

System Components

The adaptive system consists of multiple components that work together to enhance user experience. It includes a recognition platform that monitors video streams, a database for object identification, and an adaptive recommendations function that tailors suggestions based on user interactions. Users can be individuals or other systems, highlighting the flexibility of the technology in various applications.

Functionality and User Interaction

The system captures and processes user interactions to improve its adaptive capabilities. It tracks usage behaviors, categorizes interactions, and generates relationships among objects within the video stream. By leveraging this data, the adaptive system can provide personalized recommendations and enhance user engagement with content, creating a more interactive and informative viewing experience.