Video Frame Selection Using Pixel Variability Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing multimedia file representation technologies fail to consistently provide representative video frames that allow users to identify videos, as frame grabs may be uneventful or lack discernible content.
Innovation Solution
A method that divides video frames into regions, samples pixel values, and evaluates variability to determine if a frame is representative, using thresholds to select frames with sufficient variability for thumbnail representation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If frame grabs are taken from video files, then visual representation is provided, but the frames may be uneventful or lack discernible content making video identification difficult
Solution Approach 1:
The patent applies preliminary action by pre-evaluating video frames using variability metrics before selecting them as thumbnails. The system calculates pixel variability, edge density, and color diversity for each frame in advance, storing these metrics to quickly identify representative frames without needing to evaluate all frames at selection time. This ensures that only frames meeting predetermined thresholds for representativeness are used as video identifiers.
2Ease of manufacture
If simple frame grabs are used for video representation, then the process is simple, but the frames may not be representative of the video content
Solution Approach 1:
The patent applies parameter changes by evaluating multiple quantitative parameters of each video frame simultaneously, including pixel variability (standard deviation of pixel intensities), edge density (number of edges detected per unit area), and color diversity (variance in color channels). Frames are selected based on whether they meet predetermined thresholds for these parameters, transforming the simple frame grab process into a multi-parameter quality assessment system that ensures representativeness while maintaining automated efficiency.
Data Source
AI summary
Representing a video by a frame of the video. Processing a frame by receiving a first frame of a video; dividing the received first frame into at least one region; and for each region, obtaining a pixel value from a each of a plurality of pixels of the region; and determining variability among the obtained pixel values. For a determined variability less than a predetermined threshold, processing at least one subsequent frame.