Video Variant Matching via Black Border Removal
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Solution Overview
Problem
Video search systems face challenges in effectively matching content-identical variants of video content, particularly those with black borders, which are considered different due to variations in aspect ratio or cropping, hindering accurate detection and grouping of such variants.
Innovation Solution
An automated method generates variants of image frames by cropping black borders and compares them using a Video ACR/Image Comparison Algorithm, such as pHash, to identify matches and determine if one video is a variant of another, even if they have different aspect ratios or black borders.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If video search systems treat videos with black borders as different content due to aspect ratio variations, then each variant is uniquely identified, but content-identical variants cannot be effectively matched or grouped
Solution Approach 1:
The patent segments the video frame by detecting and removing black borders to isolate the actual content area. This segmentation allows the system to compare only the relevant content portions of videos with different aspect ratios, enabling accurate matching of content-identical variants while ignoring border differences.
Solution Approach 2:
The patent changes the parameter being compared from the entire video frame (including black borders) to only the active content area after border removal. This parameter transformation allows the system to maintain high matching accuracy for content-identical videos while becoming adaptable to various aspect ratios and black border configurations.
2Ease of manufacture
If video processing algorithms compare videos including black borders, then processing is simpler, but content-identical variants with different borders are incorrectly identified as different content
Solution Approach 1:
The patent performs preliminary action by detecting and removing black borders before the actual video content comparison. This preprocessing step ensures that subsequent matching operations work only with the relevant content areas, improving variant detection accuracy while maintaining processing efficiency through automated border detection algorithms.
Solution Approach 2:
The patent extracts and removes the black border elements from video frames, separating them from the actual content area. This extraction allows the comparison algorithm to focus solely on content-identical regions, significantly improving the reliability of variant detection without requiring complex processing of irrelevant border areas.
3Measurement precision
If the system generates multiple variants of video frames to account for black borders, then matching accuracy improves, but computational complexity increases
Solution Approach 1:
Instead of generating multiple variants of video frames with different black border configurations to test for matches, the patent inverts the approach by removing black borders from all videos first and then performing a single comparison. This inversion dramatically reduces computational complexity while maintaining high match detection accuracy, as it eliminates the need to generate and compare multiple border-variant combinations.
Data Source
AI summary
An automated method and apparatus are provided for identifying when a first video is a content-identical variant of a second video. The first and second video each include a plurality of image frames, and the image frames of either the first video or the second video include at least one black border. A plurality of variants are generated of selected image frames of the first video and the second video. The variants are then compared to each other, and the first video is identified as being a variant of the second video when at least one match is detected among the variants.