Automated Video Logging via Optical Character Recognition
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Solution Overview
Problem
Current video metadata acquisition relies on human input, which hinders the ability of content owners to process and accurately acquire metadata in a timely fashion, especially in live sports broadcasting where timely and accurate metadata is crucial for rapid search and retrieval of video clips.
Innovation Solution
An automated video logging system that uses computer vision techniques to identify and extract time-based metadata from video frames and accompanying data streams, creating a clock index file for storage in a database, allowing for the automatic detection and association of metadata with video frames.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual user input is used to associate metadata with video clips, then the quality of metadata can be maintained through human judgment, but the productivity and timeliness of metadata acquisition deteriorates due to slow processing speed
Solution Approach 1:
The patent replaces the manual mechanical process of users watching video clips and inputting metadata via keyboard and mouse with an automated computer vision system. The system uses optical character recognition (OCR) to detect and extract time information directly from video frames, substituting human visual processing and manual data entry with automated image analysis and pattern recognition algorithms.
Solution Approach 2:
The system enables the video metadata acquisition process to be self-service by automatically extracting time information from video frames without requiring human intervention. The automated logging system processes video streams, detects clock displays, extracts time data, and associates it with corresponding video frames independently, eliminating the need for users to manually watch and log metadata.
2Productivity
If automated computer vision techniques are used to extract metadata from video frames, then the productivity and timeliness of metadata acquisition improves, but the device complexity increases due to the need for advanced image processing systems
Solution Approach 1:
The patent segments the complex metadata acquisition task into distinct modular components: video frame capture, clock region detection, time information extraction via OCR, and metadata association. Each component is handled by a specialized module, making the overall system more manageable and maintainable despite the automation complexity.
Solution Approach 2:
The system introduces an intermediary OCR processing layer between the video frame input and the metadata output. This intermediary component translates visual clock displays into machine-readable time data, bridging the gap between unstructured video content and structured metadata without requiring direct complex analysis of the entire video stream.
3Device complexity
If users manually watch and input metadata, then the system complexity remains low with simple interfaces, but the loss of time increases due to the slow manual processing of video clips
Solution Approach 1:
The automated system enables continuous processing of video streams without interruption by manual operations. The computer vision system continuously analyzes video frames, detects clock information, and extracts time data in real-time as the video plays, eliminating the stop-start nature of manual metadata entry where users must pause, input data, and resume watching.
Solution Approach 2:
The system performs preliminary automatic extraction of time information from video frames before manual review or final metadata compilation is needed. By pre-processing the video stream and extracting all available time data in advance, the system reduces the subsequent workload and time required for final metadata assembly and verification.
Data Source
AI summary
Exemplary embodiments of systems and methods are provided for automatically creating time-based video metadata for a video source and a video playback mechanism. An automated logging process can be provided for receiving a digital video stream, analyzing one or more frames of the digital video stream, extracting a time from each of the one or more frames analyzed, and creating a clock index file associating a time with each of the one or more analyzed frames. The process can further provide for parsing one or more received data files, extracting time-based metadata from the one or more parsed data files, and determining a frame of the digital video stream that correlates to the extracted time based metadata.