Video Summary Generation Using Metadata Analysis
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Solution Overview
Problem
Existing camera systems face challenges in efficiently processing and summarizing video data, particularly with high-resolution raw-format videos, as manual scrubbing is time-consuming and automated processing is resource-intensive.
Innovation Solution
The system analyzes metadata from videos to identify events of interest, ranks these events, and selects relevant portions for inclusion in a video summary, which can be generated based on location, time, or user-defined criteria.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If automated video processing is used to identify the best scenes, then scene identification accuracy is improved, but resource consumption increases
Solution Approach 1:
The patent segments video processing into two distinct phases: a lightweight pre-processing phase that generates metadata summaries (location, time, weather, activity data) and a secondary automated processing phase that uses this metadata to identify events of interest. This segmentation allows the system to perform accurate scene identification by focusing automated analysis on metadata patterns rather than processing entire high-resolution video streams, thereby reducing computational resources while maintaining identification accuracy.
Solution Approach 2:
The system performs preliminary action by generating and storing metadata summaries during or immediately after video capture, before the actual scene identification process. This preliminary metadata extraction includes location information, time stamps, weather conditions, and detected activities, which are then used to efficiently identify events of interest without requiring intensive processing of the full video content, thus reducing resource consumption while preserving identification capability.
2Use of energy by moving object
If manual scrubbing is used to identify the best scenes, then processing resources are conserved, but time consumption increases
Solution Approach 1:
The patent introduces metadata summaries as an intermediary layer between raw video data and scene identification. Instead of directly processing high-resolution video files or relying on manual scrubbing, the system uses pre-generated metadata (containing location, time, weather, and activity information) as a mediator to efficiently identify events of interest. This intermediary approach consumes minimal processing resources while dramatically reducing the time required to locate and select the best scenes compared to manual methods.
3Manufacturing precision
If high-resolution raw-format video data is processed, then video quality is improved, but processing complexity increases
Solution Approach 1:
The patent extracts and separates metadata information (location, time, weather, activity data) from the main video processing workflow. By taking out this contextual information and processing it independently to identify events of interest, the system avoids the complexity of analyzing high-resolution raw video data directly. The extracted metadata serves as a simplified representation that guides scene selection while preserving the ability to output high-quality video segments without inheriting the full processing complexity of the source material.
Data Source
AI summary
Video and corresponding metadata is accessed. Events of interest within the video are identified based on the corresponding metadata, and best scenes are identified based on the identified events of interest. A video summary can be generated including one or more of the identified best scenes. The video summary can be generated using a video summary template with slots corresponding to video clips selected from among sets of candidate video clips. Best scenes can also be identified by receiving an indication of an event of interest within video from a user during the capture of the video. Metadata patterns representing activities identified within video clips can be identified within other videos, which can subsequently be associated with the identified activities.