Adaptive Frame Sampling for Egocentric Video Stabilization
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Solution Overview
Problem
Egocentric videos from body-worn cameras are challenging to navigate due to their length and camera shake, which existing fast forward methods fail to address effectively, as they do not account for the unique characteristics of these videos.
Innovation Solution
An adaptive frame sampling method that formulates video stabilization as an energy minimization problem, using a directed acyclic graph to select frames that minimize deviation from the camera's moving direction, thereby producing a more stable fast-forwarded video.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If uniform frame sampling is used for fast forward, then the video playback speed increases, but the camera shake induced by natural head motion further disturbs viewing
Solution Approach 1:
The patent applies local quality by differentiating frame selection based on local scene characteristics. It computes scene motion and scene complexity metrics for different video segments, then applies different sampling densities to different segments. Stationary scenes receive sparser sampling (higher speed up) while dynamic scenes receive denser sampling (lower speed up), resolving the contradiction between playback speed and viewing stability.
Solution Approach 2:
The patent implements dynamics by making the frame sampling rate adaptive rather than static. The sampling density dynamically adjusts based on real-time analysis of scene motion and scene complexity. This dynamic adaptation allows the system to optimize both playback speed and viewing stability for each specific video segment, rather than applying a uniform sampling rate throughout.
2Stability of the object's composition
If denser frame sampling is used to reduce camera shake, then viewing stability improves, but the video length increases and cognitive load increases
Solution Approach 1:
The patent applies local quality by differentiating frame selection based on local scene characteristics. It computes scene motion and scene complexity metrics for different video segments, then applies different sampling densities to different segments. Stationary scenes receive sparser sampling (higher speed up) while dynamic scenes receive denser sampling (lower speed up), resolving the contradiction between playback speed and viewing stability.
Solution Approach 2:
The patent implements partial action by applying full stabilization only where necessary. Instead of uniformly applying dense sampling throughout the entire video, it selectively applies denser sampling only to segments with high scene motion or complexity, while using sparser sampling in stable segments. This partial application reduces overall video duration while maintaining viewing stability where needed.
3Adaptability or versatility
If adaptive fast forward adjusts sampling rate based on scene motion and complexity, then cognitive load is equalized, but the device complexity increases
Solution Approach 1:
The patent applies segmentation by dividing the video into distinct segments based on scene motion and complexity thresholds. This segmentation allows the system to process and analyze video content in manageable chunks, applying different sampling strategies to each segment. The segmentation approach reduces overall processing complexity by breaking down the adaptive fast forward problem into smaller, more tractable sub-problems.
Solution Approach 2:
The patent implements parameter changes by dynamically adjusting the frame sampling rate based on computed scene motion and scene complexity parameters. The system monitors these parameters in real-time and modifies the sampling density accordingly, enabling cognitive load adaptation without requiring complex artificial intelligence models. This parameter-based approach balances adaptability with computational efficiency.
Data Source
AI summary
A method and a system for generating adaptive fast forward of egocentric videos are provided here. The method may include the following steps: obtaining a video footage containing a sequence of image frames captured by a non-stationary capturing device; estimating a moving direction of the non-stationary capturing device for a plurality of frames in the sequence of image frames; and generating a shortened video footage having fewer frames than said video footage, by sampling the sequence of image frames, wherein the sampling is carried out by selecting specific image frames and that minimize an overall cost associated with a deviation from a specific direction related to the moving direction, calculated for each of said plurality of image frames.