Multimedia Key Point Signature for Pattern Recognition
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Solution Overview
Problem
Existing multimedia data analysis solutions are inefficient in identifying unknown content elements and are sensitive to minor changes, relying heavily on metadata and analyzing every pixel, which consumes significant computing resources and may not capture all relevant information.
Innovation Solution
A method and system that determine common patterns in multimedia data elements by identifying candidate key points, analyzing their properties, selecting key points based on comparison, generating signatures, and comparing these signatures to output common patterns, thereby reducing unnecessary analysis and improving recognition accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing solutions analyze every pixel of multimedia content to identify content elements, then identification completeness is improved, but computing resource consumption increases significantly
Solution Approach 1:
The patent segments the multimedia content into discrete key points rather than analyzing every pixel. Each key point is a representative sample that captures local characteristics, allowing the system to identify content elements by comparing key points rather than processing the entire image data.
Solution Approach 2:
The patent extracts only the essential key points from the multimedia content for analysis. By selecting representative key points that capture the identity characteristics of content elements, the system removes unnecessary data (non-key point pixels) while preserving the information needed for accurate identification.
2Measurement precision
If existing solutions compare portions of multimedia content to known content elements, then recognition accuracy for known elements is improved, but ability to identify unknown elements deteriorates
Solution Approach 1:
The patent performs preliminary extraction of key points and generation of content element models before actual identification occurs. By pre-processing the content to identify and store characteristic key points, the system can efficiently match both known and unknown elements without requiring exhaustive comparison.
Solution Approach 2:
The patent creates a simplified representation (copy) of content elements through key point extraction. This key point-based model serves as a compact identifier that can be compared efficiently, allowing the system to recognize both familiar patterns and novel elements that differ from stored examples.
3Ease of operation
If existing solutions rely on metadata to identify multimedia content elements, then ease of operation is improved, but measurement precision deteriorates due to insufficient metadata definition
Solution Approach 1:
The patent introduces key points as an intermediary representation between the raw multimedia content and the identification process. These key points serve as a bridge that captures essential visual characteristics without requiring complex metadata, enabling both ease of operation and high precision through direct visual feature comparison.
Solution Approach 2:
The patent replaces the metadata-based identification system with a direct visual feature comparison system. Instead of relying on predefined metadata categories that may not capture all aspects, the system uses key point extraction and comparison to directly identify content elements based on their visual characteristics.
4Measurement precision
If existing solutions are highly sensitive to changes in received multimedia content, then measurement precision for exact matches is improved, but reliability deteriorates due to inability to handle minor variations
Solution Approach 1:
The patent applies local quality analysis by examining the characteristics of individual key points within the multimedia content. Each key point is analyzed for its local visual features, allowing the system to identify content elements based on their distinctive local characteristics rather than requiring perfect global matches.
Solution Approach 2:
The patent uses parameter-based comparison of key point characteristics to determine content element identity. By comparing parameters such as color, shape, and position of key points, the system can identify content elements while tolerating minor variations in these parameters, achieving both precision and robustness.
Data Source
AI summary
A system and method for method for determining common patterns based on key points in multimedia data elements (MMDEs). The method includes: identifying a plurality of candidate key points in each of the plurality of MMDEs, wherein a size of each candidate key point is equal to a predetermined size and a scale of each candidate key point is equal to a predetermined scale; analyzing the identified candidate key points to determine a set of properties for each candidate key point; comparing the sets of properties of the plurality of candidate key points of each MMDE; selecting, for each MMDE, a plurality of key points from among the candidate key points based on the comparison; generating, based on the key points for each MMDE, a signature for the MMDE; and comparing the signatures of the plurality of MMDEs to output at least one common pattern among the plurality of MMDEs.