Unique Media Identifier Generation for Camera Video Organization
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Solution Overview
Problem
The existing video capture and processing technologies face challenges in efficiently organizing and managing large numbers of media files generated by multiple cameras, making it difficult for users to share interesting moments due to tedious manual navigation and lack of user-friendly storage paradigms.
Innovation Solution
A system and method for generating unique media identifiers by hashing extracted data objects combining video or image data with metadata, which are stored and used to associate media files, facilitate organization, editing, and sharing by enabling automatic identification and grouping of related media.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If multiple cameras are used to capture scenes from different viewpoints, then the quantity of captured media increases, but the complexity of organizing and managing media files increases
Solution Approach 1:
The patent introduces media identifiers as an intermediary element that mediates between the large quantity of media files and the user's need to organize them. These identifiers serve as a bridging mechanism that automatically links related media files from multiple cameras without requiring direct user intervention in the organization process.
Solution Approach 2:
The system implements self-service organization by automatically generating media identifiers and associating them with the appropriate media files. This automated self-organization mechanism eliminates the need for manual file sorting and categorization, allowing the system to manage its own growing collection of media files independently.
2Ease of operation
If manual navigation through file folders is used to select media, then users can organize media files, but the time required for organization increases
Solution Approach 1:
The patent replaces the mechanical interaction of manual file folder navigation with an automated information processing system. Instead of users physically navigating through folders, the system automatically generates and processes media identifiers to organize files, substituting manual mechanical operations with automated computational processes.
Solution Approach 2:
The system extracts essential identifying information from media files to create compact media identifiers. This extraction process removes the need for users to deal with complex file paths and folder structures, isolating only the critical identifying elements needed for organization and retrieval.
3Productivity
If media files are not organized automatically, then storage flexibility is maintained, but user productivity in sharing media decreases
Solution Approach 1:
The system performs preliminary organization actions by generating media identifiers and associating them with files at the time of capture or import. This advance organization prepares the media collection for future sharing and retrieval operations, eliminating the need for later manual sorting and improving overall productivity.
Solution Approach 2:
The media identifier system serves multiple functions simultaneously: it organizes files, enables rapid retrieval, facilitates sharing, and maintains storage flexibility. This multi-functional approach increases productivity across various media management tasks without requiring separate systems for each function.
Data Source
AI summary
A video identifier uniquely identifying a video captured by a camera is generated. The video includes video frames and optionally concurrently captured audio as well as video metadata describing the video. Video data is extracted from at least two of the video's frames. By combining the extracted video data in an order specified by an identifier generation protocol, an extracted data object is generated. The extracted data object is hashed to generate the unique media identifier, which is stored in association with the video. The identifier generation protocol may indicate the portions of the video data to extract, such as video data corresponding to particular video frames and audio data corresponding to particular audio samples. The extracted data object may include a size of particular video frames, a number of audio samples in the video, or the duration of the video, for example.