Automated Detection of Animated Problem Indicators in Display Video
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Solution Overview
Problem
Identifying visual problem indicators on a computing system's display, such as buffering issues, can be challenging for automated systems without manual intervention, as these indicators are often animated and require human interpretation.
Innovation Solution
An automated analysis method that detects frame-over-frame pixel changes in recorded video to identify animated problem indicators, such as buffering indicators, by determining motion scores and shape matching within specific areas of the screen, allowing for automated detection and tagging of issues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated systems attempt to identify visual problem indicators on display screens, then testing efficiency and productivity are improved, but the ability to accurately detect animated problem indicators deteriorates without manual intervention
Solution Approach 1:
The system dynamically adapts its detection approach by analyzing frame-over-frame changes to identify animated indicators. The motion detection capability allows the system to track moving visual elements across multiple frames, enabling automated identification of animated problem indicators that would be difficult to detect in static images, thus resolving the contradiction between automation and detection accuracy.
Solution Approach 2:
The patent replaces manual visual inspection with an automated computer vision system that uses image processing algorithms to detect and analyze problem indicators. This substitution of mechanical/manual detection with automated optical analysis enables both high productivity and maintained measurement precision through systematic frame comparison and motion pattern recognition.
2Measurement precision
If manual intervention is used to identify problem indicators, then detection accuracy is improved, but productivity and automation level deteriorate
Solution Approach 1:
The system performs self-service by automatically detecting, analyzing, and identifying problem indicators without requiring manual intervention. The automated video analysis system processes frames, detects motion patterns, and identifies animated indicators independently, maintaining detection accuracy while eliminating the need for human reviewers, thus resolving the contradiction between precision and productivity.
Solution Approach 2:
The patent introduces an intermediary automated analysis system that acts as a bridge between the visual display and the testing process. This intermediary system processes video frames and extracts problem indicator information, replacing direct manual inspection while maintaining accurate detection through sophisticated image processing and motion analysis algorithms.
3Difficulty of detecting and measuring
If video analysis is performed frame-over-frame to detect motion, then detection capability for animated indicators is improved, but computational complexity and device complexity increase
Solution Approach 1:
The system segments the video analysis process into distinct stages: frame capture, motion detection through frame comparison, pattern recognition, and indicator identification. This segmentation of the analytical process allows for efficient processing at each stage, reducing overall computational complexity while maintaining high detection capability for animated problem indicators.
Solution Approach 2:
The patent applies partial action by focusing computational resources only on detecting motion in regions where problem indicators are likely to appear, rather than analyzing every pixel in every frame. This selective approach maintains high detection capability for animated indicators while significantly reducing the overall computational burden and device complexity required.
Data Source
AI summary
Systems, methods, and computer-readable media are described for performing automated analysis of frame-over-frame pixel changes in recorded video of the display output of a computing device to determine whether the computing device presented an animated buffering indicator or other animated problem indicator. A system may be configured to detect motion by determining frame-over-frame pixel intensity changes at various pixel locations across a number of frames, then to determine whether the pixel locations that suggest motion (such as those pixel locations that had sufficient intensity change when accounting for potential noise in the video data) are concentrated in an area of the screen in which problem indicators are expected to be displayed. The system may then determine whether the shape of the pixel locations that indicated sufficient motion match an expected shape or path of motion for a given class of problem indictors.