Geometric Primitive Background Identification in Video Persona Extraction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing video extraction technologies face challenges in accurately and precisely isolating a user's persona from video feeds, particularly in identifying background regions, which is crucial for comprehensive user extraction and enhancing multimedia communication experiences.
Innovation Solution
The use of geometric primitives and novel processing techniques to identify and classify background regions in video data, employing alpha masks and background-color models to distinguish between persona and background pixels, facilitating more accurate persona extraction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional video extraction methods are used to isolate user persona from video feeds, then the extraction process can be performed, but the accuracy and precision of background identification is insufficient
Solution Approach 1:
The patent segments the video data into distinct geometric primitive regions (walls, floors, ceilings, windows, doors) and processes each segment with appropriate background identification techniques. This segmentation allows for more precise background identification by treating different spatial regions separately, thereby resolving the contradiction between measurement precision and reliability in persona extraction.
Solution Approach 2:
The patent introduces geometric primitives as intermediary elements between the raw video data and the final persona extraction. These primitives serve as mediators that structure the background information, making it easier to identify and separate from the user persona, thus improving both background identification accuracy and persona extraction precision simultaneously.
2Manufacturing precision
If geometric primitives are used to identify background regions, then the precision of persona extraction is improved, but the processing complexity increases
Solution Approach 1:
The patent changes the parameter representation of video data by describing background regions in terms of geometric primitives (planes, surfaces, volumes) rather than raw pixel data. This parameter transformation simplifies the mathematical operations required for background identification while maintaining high precision in persona extraction, effectively resolving the contradiction between extraction precision and processing complexity.
3Reliability
If comprehensive background identification is performed using geometric primitives, then the quality of multimedia communication is enhanced, but the processing time is increased
Solution Approach 1:
The patent performs preliminary action by pre-identifying and structuring background regions using geometric primitives before the actual persona extraction process. By preparing the background information in advance with a structured geometric representation, the system reduces the computational burden during real-time processing, thereby enhancing multimedia communication quality without excessive processing time delays.
Data Source
AI summary
Systems and methods for using geometric primitives to identify background in video data. In one embodiment, a method obtains video data depicting at least a portion of a user. The video data is processed with at least one persona identification module comprising a geometric primitive module for generating a first persona probability map at least in part by: detecting at least one geometric primitive within the video data; identifying a respective region within the video data associated with each of the at least one detected geometric primitives; and assigning the respective regions an increased background-probability in the first persona probability map; and outputting a persona image by extracting pixels from the video data based on the persona probability map.