Textless Video Matching via Shot Sequence Analysis
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Solution Overview
Problem
Manual methods for matching textless material to corresponding texted material in video content are time-consuming, inefficient, and prone to human error, hindering the speed and accuracy of video distribution in multiple languages.
Innovation Solution
A video processing system with a textless matching system that automatically segments video content into shots, identifies sequences with similar durations, compares image content using representative frames, and pairs texted and textless elements for automated replacement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual methods are used to match textless material to texted material, then matching accuracy can be maintained through human judgment, but the process becomes time-consuming and reduces productivity
Solution Approach 1:
The patent replaces manual visual inspection and matching (mechanical human operation) with an automated computer-based system that uses image processing algorithms to compare frames, detect text regions, and identify matching sequences. This substitution enables high-speed automated processing while maintaining consistent accuracy through algorithmic comparison of visual features.
2Productivity
If automated matching systems are implemented to increase productivity, then processing speed improves, but the system complexity increases
Solution Approach 1:
The patent segments the video matching task into distinct modular components: frame extraction, text region detection, image feature comparison, sequence duration analysis, and matching decision. Each module handles a specific aspect of the problem independently, which simplifies the overall system design and makes the complexity manageable through division of functions.
Solution Approach 2:
The patent introduces intermediary elements such as representative frames extracted from video sequences and detected text region masks as intermediate representations. These intermediaries bridge the gap between raw video data and final matching decisions, enabling the system to process complex video content through simplified intermediate stages that reduce overall system complexity.
3Device complexity
If manual matching is used, then system complexity remains low, but human error increases and reliability decreases
Solution Approach 1:
The patent replaces manual matching operations with automated computer-based image processing and comparison algorithms. This substitution eliminates human fatigue, inconsistency, and errors associated with manual visual inspection, thereby significantly improving reliability and reducing error rates in the matching process.
Solution Approach 2:
The patent implements feedback mechanisms where the automated system continuously compares extracted features against established criteria and adjusts matching decisions based on quantitative analysis of image similarities and text region correspondences. This feedback-driven approach ensures consistent and reliable matching results without human intervention.
4Measurement precision
If automated image comparison is performed on all frames, then matching accuracy improves, but computational energy consumption increases
Solution Approach 1:
The patent extracts and processes only the essential visual features and text regions from video frames rather than analyzing complete frame data. By extracting representative features such as text region boundaries, key visual descriptors, and sequence duration metrics, the system achieves accurate matching with reduced computational energy consumption.
Solution Approach 2:
The patent applies partial action by performing detailed image comparison only on selected representative frames and identified text regions rather than processing every pixel of every frame. This selective processing approach maintains matching accuracy for critical elements while significantly reducing overall computational energy requirements.
Data Source
AI summary
Systems, methods, and a computer-readable medium are provided for matching textless elements to texted elements in video content. A video processing system including a textless matching system may divide a video into shots, identify shots having similar durations, identify sequences of shots having similar durations, and compare image content in representative frames of the sequences to determine whether the sequences match. When the sequences are determined to match, the sequences may be paired, wherein the first sequence may include shots with overlaid text and the second sequence may include textless version of corresponding texted shots included in the first sequence. In some examples, the video processing system may further replace the determined corresponding texted shots.