Multimedia Query System Using Anchor Point Metadata Extraction
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Solution Overview
Problem
Current multimedia data capture and storage systems face challenges in efficiently processing and querying large volumes of raw multimedia data, particularly in systems with limited local storage and processing capacities, leading to high processing times and power consumption.
Innovation Solution
A multimedia query system that extracts anchor point metadata from raw multimedia data using AI/ML models, allowing for efficient storage and querying by identifying relevant data candidates through metadata search, reducing the need for extensive raw data processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If all raw multimedia data is stored and processed, then query accuracy is improved, but processing time and power consumption increase significantly
Solution Approach 1:
The system extracts anchor point metadata from raw multimedia data, separating essential search-relevant information from the complete raw data. This extraction allows the system to work with a reduced data subset for queries, maintaining accuracy while reducing processing time and power consumption.
Solution Approach 2:
The multimedia data is segmented into anchor points (metadata) and full raw data. The anchor points serve as indexed references that can be queried independently, allowing the system to avoid processing entire raw multimedia files unless necessary, thus reducing processing time while maintaining query accuracy.
2Ease of operation
If all raw multimedia data is stored locally, then data accessibility is improved, but storage capacity requirements increase
Solution Approach 1:
The system extracts and stores only anchor point metadata locally, removing the requirement to store complete raw multimedia data locally. This extraction approach maintains data accessibility through metadata indexing while dramatically reducing local storage capacity requirements.
Solution Approach 2:
Anchor point metadata acts as an intermediary between the query system and the full raw multimedia data. The metadata can be stored and processed locally for quick access, while the actual raw data can reside remotely, reducing local storage requirements while maintaining accessibility.
3Loss of information
If complete raw multimedia data is processed for queries, then information completeness is improved, but power consumption increases
Solution Approach 1:
The system extracts anchor point metadata that contains essential information for query processing, removing the need to process complete raw multimedia data. This extraction maintains information completeness for search purposes while significantly reducing power consumption.
Solution Approach 2:
The system performs partial processing by working with anchor point metadata rather than complete raw data. This partial action is sufficient for most query operations, reducing power consumption while maintaining adequate information completeness for the intended use case.
4Speed
If metadata extraction and indexing is implemented, then query speed is improved, but system complexity increases
Solution Approach 1:
The system performs preliminary action by extracting and indexing anchor point metadata in advance, before queries are executed. This pre-processing creates a ready-to-search structure that dramatically improves query speed, while the automation of the extraction process manages system complexity.
Data Source
AI summary
A multimedia query system is described that includes a multimedia capture system configured to capture raw multimedia data comprising at least one of raw video data or raw audio data, a metadata engine configured to extract one or more anchor points of metadata from the raw multimedia data and to store the one or more anchor points of metadata, wherein the anchor points of metadata includes references to respective portions of the raw multimedia data. The multimedia query system further includes a storage engine configured to store the raw multimedia data, a recall engine configured to receive a query and to apply the query to the one or more anchor points of metadata to identify one or more raw multimedia data candidates from the portions of the raw multimedia data, and a query engine configured to generate a response to the query based on the one or more raw multimedia data candidates.