Object-Based Video Metadata Search for Faster Forensic Review
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Solution Overview
Problem
Forensic investigations based on video imagery are inefficient due to the need to consider temporal metadata for each frame to determine the presence of objects with specific characteristics, making the process time-consuming.
Innovation Solution
The creation and use of an object-based metadata database that aggregates identification information for video images, allowing rapid identification of objects with specified attributes and facilitating efficient forensic searching and triggering of alerts based on object attributes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If temporal metadata for each video frame is manually reviewed to identify objects with specific characteristics, then comprehensive search coverage is achieved, but the investigation process becomes time-consuming and inefficient
Solution Approach 1:
The system performs preliminary processing of video frames to extract object characteristics and store them in a metadata database before the actual investigation query is executed. This pre-extraction and pre-storage of object attributes (such as color, shape, size, position) allows investigators to quickly query pre-processed data rather than manually examining each frame, significantly reducing investigation time while maintaining accurate object identification
Solution Approach 2:
The system creates a copy of essential object information from video frames in the form of structured metadata records. These metadata copies contain key object characteristics extracted from each frame and are stored in a searchable database, enabling rapid querying without requiring access to the original video frames during the investigation process
2Reliability
If all video frames are examined to ensure no object of interest is missed, then detection completeness is achieved, but processing complexity and time increase significantly
Solution Approach 1:
The system segments the video analysis task by separating object detection and characteristic extraction into distinct processing stages. Each video frame is processed to identify objects and extract their attributes, with results stored as separate metadata records. This segmentation allows the system to maintain comprehensive detection while organizing data in a manageable, query-efficient structure that reduces overall processing complexity
Solution Approach 2:
The system introduces a metadata database as an intermediary layer between video frame processing and investigation queries. This intermediary stores pre-extracted object characteristics and enables efficient searching without requiring direct analysis of video frames during query execution, thereby reducing processing complexity while maintaining detection completeness
Data Source
AI summary
An example method of operating a computing apparatus, which comprises: obtaining, via a graphical user interface, user input indicative of a query relating to a video image of a scene captured by a camera; accessing an object stream data store comprising a plurality of object-based metadata records, each object-based metadata record of the plurality of object-based metadata records associated with a corresponding object depicted in video images captured by the camera and comprising at least one object stream comprising (i) an object identifier (ID) and (ii) one or more object attributes associated with the corresponding object, the object stream data store comprising aggregated identification information for video images in which the corresponding object was detected; identifying, based on the query, an object of interest from amongst objects depicted in the video images captured by the camera, the object of interest associated with a particular object-based metadata record; obtaining, from the object stream, additional information pertaining to the object of interest; and presenting, via the graphical user interface, at least the additional information.