Video Summarization via Segmented Ingestion and Annotation
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Solution Overview
Problem
The existing video editing processes are time-consuming and require specialized software, making it inefficient to condense lengthy video data into a short summary highlighting interesting events, especially when capturing wide fields of view over extended periods.
Innovation Solution
A system that captures video data, breaks it into sections, annotates them using computer vision and additional data, and generates a video summarization by identifying interesting moments and prioritizing them to create a condensed summary suitable for various viewing devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional video editing processes are used to condense lengthy video data, then the video can be edited and summarized, but the process becomes time-consuming and requires specialized software
Solution Approach 1:
The system performs automatic video analysis and summarization without requiring manual editing. The processor autonomously identifies interesting moments, segments video data, and generates condensed summaries using computer vision algorithms and metadata analysis, eliminating the need for specialized editing software and manual intervention.
Solution Approach 2:
The patent replaces manual mechanical video editing processes with automated computational methods. Instead of using traditional video editing software that requires human operators to manually review and cut footage, the system uses computer vision algorithms, machine learning models, and automated metadata processing to identify and extract interesting segments.
2Productivity
If traditional video editing processes are used, then video can be condensed, but the process complexity increases due to requiring specialized software
Solution Approach 1:
The system autonomously processes video data without requiring external specialized editing software. The integrated processor performs all necessary functions including video segmentation, interest detection, and summary generation using built-in computer vision capabilities and metadata processing, eliminating dependency on complex external tools.
Solution Approach 2:
The system integrates multiple functions into a single processing platform. The same processor that captures and stores video data also performs analysis, segmentation, and summarization tasks, eliminating the need for separate specialized editing software and reducing overall system complexity.
3Quantity of substance
If lengthy video data is captured over extended periods, then comprehensive coverage is achieved, but the data volume increases making processing inefficient
Solution Approach 1:
The system extracts only the essential and interesting portions from lengthy video data. Using computer vision algorithms and metadata analysis, it identifies and extracts key moments while discarding redundant content, maintaining comprehensive coverage of important events while reducing the volume of data requiring detailed processing.
Solution Approach 2:
The system divides lengthy video data into manageable segments based on detected interest levels and metadata markers. This segmentation allows efficient processing by handling smaller discrete units rather than processing the entire lengthy video continuously, improving overall processing efficiency while maintaining comprehensive coverage.
Data Source
AI summary
Devices, systems and methods are disclosed for reducing a perceived latency associated with uploading and annotating video data. For example, video data may be divided into video sections that are uploaded individually so that the video sections may be annotated as they are received. This reduces a latency associated with the annotation process, as a portion of the video data is annotated before an entirety of the video data is uploaded. In addition, the annotation data may be used to generate a master clip table and extract individual video clips from the video data.