Partial Decompression for Multimedia Highlight Detection
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Solution Overview
Problem
Conventional methods for finding highlighted intervals in multimedia data are inefficient, especially in mobile devices, due to the need for full decompression of files, which is time-consuming and resource-intensive, and may not accurately identify highlighted sections in sound source tracks for pre-listening services.
Innovation Solution
A method that involves partial decompression of multimedia files to extract metadata parameters, allowing for the quick identification of highlighted intervals without decompressing the entire file, reducing processing time and memory usage, and enabling the detection of highlighted sections in all sound source files, including unpopular ones without requiring internet connectivity or invading privacy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If full decompression of multimedia files is performed to accurately identify highlighted intervals, then measurement precision is improved, but processing time and resource consumption increase significantly
Solution Approach 1:
The multimedia file is divided into multiple frames, and only selected frames are decompressed for analysis. The parser divides the file into frame units, and the decompressor selectively decompresses specific frames based on metadata parameters rather than the entire file, achieving both accuracy and efficiency.
Solution Approach 2:
Metadata parameters are extracted and analyzed before full decompression to identify which frames contain highlighted intervals. This preliminary analysis using compression-domain features allows the system to target only relevant sections for decompression, avoiding unnecessary processing time.
2Adaptability or versatility
If full decompression is performed to search for highlighted intervals in all sound source files, then completeness of search is improved, but device complexity and resource usage increase
Solution Approach 1:
Instead of fully decompressing every sound source file, the system performs partial decompression of selected frames that are most likely to contain highlighted intervals. This partial action approach maintains the ability to search all files while significantly reducing processing complexity and resource requirements.
Solution Approach 2:
Metadata parameters serve as an intermediary that guides the decompression process. Rather than directly decompressing entire files, the system uses metadata to identify and decompress only the relevant frames, simplifying the overall processing complexity while maintaining comprehensive search capability.
3Ease of operation
If fixed reproduction start points are used for pre-listening service, then ease of operation is improved, but measurement precision of highlighted intervals deteriorates
Solution Approach 1:
The reproduction start point is changed from a fixed position to a dynamic position determined by analyzing metadata parameters of decompressed frames. The system identifies frames with audio features that correspond to highlighted intervals and sets those as start points, making the service both easy to operate and accurately targeted.
Data Source
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AI summary
Disclosed is a method for searching multimedia data for a highlight interval, comprising the steps of: parsing the multimedia data into at least one frame; partially decompressing the at least one frame; extracting at least one metadata parameter from the at least one partially decompressed frame; and determining a highlight interval of the multimedia data based on the at least one metadata parameter.