Significant Face Detection in Video Streams
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Solution Overview
Problem
Conventional image management tools require users to manually search through large volumes of digital photographs and video clips to locate specific individuals, which is time-consuming due to the need to open or play each media instance, especially when multiple individuals are present in each clip.
Innovation Solution
A system and method for detecting significant faces in video streams, where faces are identified, tracked, and categorized based on significance criteria such as size, focus, resolution, and movement, allowing for organization and easy browsing of video streams by significant faces rather than traditional file or folder structures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If users manually search through large volumes of digital photographs and video clips to locate specific individuals, then they can find the desired content, but the process is time-consuming
Solution Approach 1:
The system performs preliminary face detection and tracking during video stream processing, creating an organized database of faces with associated video segments before the user needs to search. This advance preparation allows users to quickly locate specific individuals without manually reviewing each video clip.
Solution Approach 2:
The patent introduces an intermediary face recognition system that acts as a mediator between the large volume of video content and the user's search query. The system detects, tracks, and organizes faces using significance criteria, creating an intermediate structured representation that enables efficient retrieval without direct user inspection of all media.
2Reliability
If users open or play each video clip to locate a particular individual, then they can identify the person, but the process becomes inefficient with large volumes of media
Solution Approach 1:
The system extracts face information from video streams and separates it from the full video content. By extracting and organizing face data with significance criteria and associated video segments, the system allows users to locate individuals directly through the organized database without playing through entire video clips.
Solution Approach 2:
The patent replaces the mechanical process of manually opening and reviewing each video clip with an automated face detection and tracking system. The computer-implemented system automatically identifies faces, applies significance criteria, and retrieves associated video segments, substituting automated digital processing for manual mechanical review.
3Ease of operation
If conventional image management tools organize photos and videos by file or folder structures, then they maintain simple organization, but users cannot efficiently browse by individual faces within media
Solution Approach 1:
The patent adds a new dimension to media organization by introducing face-based indexing alongside traditional file/folder structures. The system creates a multi-dimensional organization system where media can be accessed both by traditional paths and by detected faces, allowing users to browse video streams organized by significant faces without abandoning simple file organization.
Data Source
AI summary
Systems and methods of processing video streams are described. A face is detected in a video stream. The face is tracked to determine a video clip associated with one of a plurality of individuals. The video segment is assigned to a group of video clips based on the associated individual. A significant face is detected in the group of video clips when the detected face meets one or more significance criteria. The significance criteria describes a face-frame characteristic. A representation of the significant face is displayed in association with a representation of the group of video clips. The order of the significance criteria is adjusted through a user interface.