Video Analytics for Head-Mounted Display Training Readability
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Solution Overview
Problem
Existing training videos for field workers in industrial facilities often lack adequate readability of critical operational and maintenance tasks, necessitating an improved method for creating and modifying videos to enhance visibility and clarity, especially for use with head-mounted displays.
Innovation Solution
A method involving metadata-driven video analysis to determine key aspects of tasks, capturing supplemental videos when necessary, and mashing these with primary videos to ensure critical elements meet readability thresholds, resulting in enhanced technical guidance videos displayed on head-mounted displays.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If training videos are captured from a single angle or focal length, then the video production process is simple, but the readability of critical task elements is insufficient
Solution Approach 1:
The patent segments the video production process into multiple captured videos from different angles and focal lengths. Each video captures specific critical elements of the task, allowing the system to select and combine only the necessary segments to achieve readable views of all critical elements without producing an excessively complex multi-video setup.
Solution Approach 2:
The patent adds dimensional variety to video capture by utilizing multiple angles and focal lengths. This dimensional approach allows critical elements that may be obscured or unreadable from a single viewpoint to be captured from alternative perspectives, thereby improving readability without requiring complex post-production manipulation of a single video source.
2Measurement precision
If multiple videos are captured from different angles and focal lengths, then the readability of critical elements is improved, but the video production process becomes more complex
Solution Approach 1:
The system performs self-service by automatically analyzing captured videos to identify which critical elements are visible and readable in each video. This automated analysis eliminates the need for manual review and selection of video segments, allowing the system to efficiently determine the optimal combination of videos needed to achieve complete coverage of all critical elements.
Solution Approach 2:
The patent implements feedback mechanisms where the system evaluates the readability of critical elements in captured videos and uses this information to determine whether additional videos are needed. This feedback-driven approach ensures that video production continues only until all critical elements are adequately captured, preventing unnecessary production complexity while maintaining high readability standards.
3Measurement precision
If videos are manually reviewed and modified to improve readability, then the quality of training videos is enhanced, but the time and resources required increase
Solution Approach 1:
The patent replaces manual mechanical review processes with automated computational analysis. The system uses algorithms to automatically assess the readability of critical elements in video frames, eliminating the need for human reviewers to manually examine and evaluate each video. This substitution dramatically reduces the time and human resources required while maintaining or improving the quality of readability assessment.
Solution Approach 2:
The patent introduces an automated analysis system as an intermediary between video capture and final video production. This intermediary automatically evaluates video quality, identifies readability issues, and determines the optimal video组合, thereby eliminating the need for time-consuming manual review while ensuring consistent quality standards are met.
4Productivity
If a single video is used to capture all task elements, then the production process is efficient, but critical elements may not be visible with adequate clarity
Solution Approach 1:
The patent segments the visual information into multiple captured videos, each optimized for specific critical elements. Rather than attempting to capture all elements in a single video, the system divides the task into multiple video captures from different angles and focal lengths, ensuring that each critical element is captured with adequate clarity while maintaining overall production efficiency through automated selection and combination.
Data Source
AI summary
A method of creating and/or modifying a video for use in a head-mounted display while a user of the head-mounted display is carrying out a task that is illustrated by the video. The method may include processing an initial video to automatically determine when the initial video does not cover key aspects of the task and thus when video mashing is desired. When video mashing is desired, a supporting video is obtained to cover the missing key aspects, and the initial video and the supporting video are automatically mashed, result in a composite video for subsequent display on the head-mounted display.