GPU Scene Transition Detection for Video Playback
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Solution Overview
Problem
Current video playback systems rely on time-based controls for fast forwarding and reversing, which do not align with the natural structure of video content, making it cumbersome for users to navigate through video content based on content progression.
Innovation Solution
A system that generates a list of content-based scene transitions by computing correlation coefficients between video frames using a video decoder engine and frame correlation engine, allowing for content-based reverse functionality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If time-based fast forward and reverse controls are used, then playback speed can be increased or reversed, but the navigation does not align with the natural structure of video content
Solution Approach 1:
The video content is segmented into discrete scenes based on visual changes detected through frame correlation analysis. This segmentation allows the playback system to navigate between meaningful content units rather than simply advancing by time intervals, making fast forward and reverse operations align with the natural structure of the video content.
2Adaptability or versatility
If chapters are used to organize video content, then users can select specific sections to view, but the granularity is too large for useful fast forward or reverse application
Solution Approach 1:
The scene segmentation is performed dynamically during playback based on real-time frame correlation analysis, rather than using pre-defined static chapters. This dynamic approach creates a fine-grained structure that adapts to the actual content changes in the video, enabling meaningful fast forward and reverse operations at the scene level rather than at the chapter level.
3Adaptability or versatility
If scene transition detection is performed in real-time, then content-based navigation is enabled, but processing complexity increases
Solution Approach 1:
The patent replaces complex CPU-based frame comparison operations with GPU-based parallel processing. The GPU's architecture is better suited for the pixel-by-pixel correlation calculations required for scene detection, reducing the processing burden on the main system and enabling real-time scene transition detection without excessive complexity.
Solution Approach 2:
The patent introduces an intermediary frame buffer system that stores decoded video frames for comparison. This frame buffer acts as a mediator between the video decoder and the scene detection algorithm, allowing efficient access to previous frames for correlation calculations without requiring complex memory management or data transformation operations.
Data Source
AI summary
One embodiment of the present invention sets forth a technique that enables a user to reverse through video content based on scene transitions. By employing a graphics processing unit to compute one or more frame-to-frame correlation coefficients that measure the consistency of sequential images and a central processing unit to analyze the one or more correlation coefficients, a list of scene transitions may be generated in real-time. The list of scene transitions forms the basis for a content-based reverse user control within the playback application. The content-based reverse user control enables a more natural mechanism for reversing through video content, providing the user with a superior overall viewing experience.