Object-Based Metadata Database for Video Forensic Search
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Solution Overview
Problem
Forensic investigations involving video imagery are inefficient due to the need for investigators to manually search through temporal metadata for specific objects across numerous video frames, making the process time-consuming and labor-intensive.
Innovation Solution
A method of creating an object-based metadata database that aggregates temporal metadata from video frames, allowing for the identification and storage of objects with specific attributes, enabling efficient retrieval of relevant frames by matching object IDs and attribute combinations, and providing a thumbnail image representative of detected objects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If investigators manually search through temporal metadata for each video frame to find specific objects, then they can identify objects with specific characteristics, but the investigative process becomes time-consuming and inefficient
Solution Approach 1:
The system performs preliminary processing by automatically extracting and aggregating temporal metadata from all video frames before the investigator needs to search. Object detection, attribute extraction, and metadata aggregation are completed in advance, creating a pre-processed database that allows instant retrieval of relevant frames without manual frame-by-frame analysis.
Solution Approach 2:
The patent introduces an intermediary metadata aggregation system that acts as a mediator between the raw video frames and the investigator's search queries. This intermediary layer processes and organizes temporal metadata, creating a structured database that enables efficient object-based search without requiring direct manual examination of each frame.
2Reliability
If the system stores and processes temporal metadata for every video frame, then complete object detection information is available, but the data volume and processing complexity increase significantly
Solution Approach 1:
The system merges and aggregates temporal metadata from multiple video frames into a single object-based record. Instead of storing and processing each frame's metadata separately, the system combines detection information, attributes, and temporal data into unified object records, reducing overall data complexity while maintaining complete detection information.
Solution Approach 2:
The metadata aggregation system serves multiple functions simultaneously: it extracts object information, aggregates temporal data, creates searchable indexes, and prepares retrieval queries. This multi-functional approach reduces processing complexity by consolidating multiple operations into a single streamlined pipeline.
3Reliability
If investigators review entire video streams or metadata databases manually to find specific objects, then they can ensure no details are missed, but the process becomes labor-intensive and inefficient
Solution Approach 1:
The system extracts only the relevant temporal metadata and object information from the entire video stream, separating useful data from unnecessary content. By extracting and aggregating only the metadata related to detected objects and their attributes, the system enables investigators to access specific information directly without manually reviewing entire video streams.
Solution Approach 2:
The system creates a copied and organized version of the temporal metadata in an object-based database structure. This metadata copy is pre-processed and indexed, allowing investigators to search and retrieve information efficiently without working with the original raw video data or unprocessed metadata.
Data Source
AI summary
A method of operating a computing apparatus, which comprises: accessing a plurality of temporal metadata datasets, each of the plurality of temporal metadata datasets associated with a video image frame of a scene and comprising (i) identification information for that video image frame; (ii) an object identifier (ID) for each of one or more objects detected in that video image frame; and (iii) one or more object attributes associated with each of the one or more objects detected in that video image frame; for a particular object having an object ID, identifying a subset of temporal metadata datasets in the plurality of temporal metadata datasets comprising an object ID that matches the object ID of the particular object, and processing the subset of temporal metadata datasets to create an object-based metadata record for the particular object, the object-based metadata record for the particular object comprising (i) the object ID; (ii) one or more object attributes associated with the particular object; and (iii) aggregated identification information for video image frames in which the particular object was detected; and causing the object-based metadata record to be stored in an object-based metadata database.