Context-Aware Video Progress Bar Scene Proportion Timeline
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Solution Overview
Problem
Conventional video-player systems suffer from imprecise scrubbing through videos due to rigid and undifferentiated video scrubbers, which fail to accurately represent scene changes, making it difficult for users to navigate and identify specific frames or scenes.
Innovation Solution
A context-aware-video-progress bar is introduced, featuring a video-scene-proportionate timeline with time-interval sections sized according to relative scene proportions, allowing for more precise navigation and identification of frames or scenes by dynamically adjusting section sizes based on scene density.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a conventional video scrubber is used, then the video player can navigate through videos, but the scrubbing precision is poor due to rigid and undifferentiated timeline sections
Solution Approach 1:
The video timeline is segmented into multiple time-interval sections, where each section corresponds to a specific scene or segment of the video. These sections are divided based on scene boundaries detected through image feature analysis, allowing the scrubber to navigate through distinct video segments with improved precision and user control.
Solution Approach 2:
Different time-interval sections of the scrubber are given different visual properties and interactions based on their corresponding video content. Sections with higher scene density or importance can be highlighted or expanded, while less important sections are compressed, creating a non-uniform timeline that reflects the actual content distribution and improves navigation efficiency.
2Loss of information
If a uniform timeline is used in the video progress bar, then the scrubber structure is simple, but it fails to accurately represent scene changes and proportions
Solution Approach 1:
The timeline structure is made dynamic and adaptive rather than static and uniform. The system automatically adjusts the duration and visual representation of time-interval sections based on the detected scene proportions and content density. This dynamic adjustment ensures that the timeline accurately reflects the actual scene distribution in the video without requiring manual configuration.
Solution Approach 2:
The system performs preliminary analysis of the video content to detect scene boundaries and calculate scene proportions before generating the scrubber timeline. This pre-processing step allows the timeline to be pre-configured with accurate scene-based segments, enabling improved navigation from the start without requiring real-time computation during user interaction.
3Productivity
If conventional video scrubbers are used, then navigation is possible, but user effort and time are increased due to inability to quickly identify scenes
Solution Approach 1:
Different time-interval sections are visually differentiated using color coding or visual indicators that represent different scenes or content types. This visual encoding allows users to quickly identify and navigate to specific scenes without having to manually scan through the entire timeline, significantly reducing the time required to locate desired content.
Solution Approach 2:
The scrubber interface incorporates additional visual dimensions beyond the simple linear timeline, such as vertical scene indicators, thumbnail previews, or hierarchical scene grouping. This multi-dimensional presentation provides users with more information about video content structure, enabling faster scene identification and navigation through the video.
Data Source
AI summary
This disclosure relates to methods, non-transitory computer readable media, and systems that can generate a context-aware-video-progress bar including a video-scene-proportionate timeline with time-interval sections sized according to relative scene proportions within time intervals of a video. In some implementations, for instance, the disclosed systems determine relative proportions of scenes within a video across time intervals of the video and generate a video-scene-proportionate timeline comprising time-interval sections sized proportionate to the relative proportions of scenes across the time intervals. By integrating the video-scene-proportionate timeline within a video-progress bar, the disclosed systems generate a context-aware-video-progress bar for a video. Such a context-aware-video-progress bar can facilitate more precise and intelligent scrubbing through a video, a dynamic graphical user interface for navigating within and identifying frames of the video, and a flexible user-friendly tool for quickly identifying scenes.