Timelapse Video Reframing to Preserve User Strokes
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Solution Overview
Problem
Conventional video editing tools fail to account for user strokes and actual focus points when resizing or cropping videos to different aspect ratios, leading to decreased user experience and content quality, particularly in timelapse videos.
Innovation Solution
A video processing apparatus that computes a cost function based on user strokes and salient information to generate a modified output video with a different aspect ratio, preserving essential user interactions and focus points.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional video editing tools resize or crop videos to different aspect ratios, then the aspect ratio is changed, but user strokes and focus points are lost or misplaced
Solution Approach 1:
The system performs preliminary analysis of user strokes and salient information before resizing or cropping the video. By pre-identifying the locations and importance of user interactions, the system can plan the reframing operation to preserve these elements in the output video, rather than losing them during the aspect ratio conversion.
Solution Approach 2:
The system uses a cost function that incorporates feedback from user stroke locations and salient information to evaluate potential reframing options. This feedback mechanism allows the system to iteratively adjust the framing to maximize preservation of important content while achieving the target aspect ratio, resolving the contradiction between adaptability and information loss.
2Adaptability or versatility
If conventional video editing tools crop videos to fit different aspect ratios, then the aspect ratio is changed, but content quality and user experience decrease
Solution Approach 1:
The cost function incorporates quality metrics that provide feedback on how well important content is preserved during reframing. By continuously evaluating the quality impact of different cropping decisions based on user strokes and salient information, the system maintains higher content quality in the output video while adapting to the target aspect ratio.
Solution Approach 2:
The system changes multiple parameters simultaneously during reframing, including crop position, scale, and rotation, optimized by the cost function. This multi-parameter adjustment allows the system to achieve the target aspect ratio while preserving content quality better than simple cropping methods.
3Manufacturing precision
If manual editing is used to preserve user strokes during aspect ratio conversion, then content quality is maintained, but editing time increases
Solution Approach 1:
The system performs the complex reframing operation automatically using the cost function optimization, eliminating the need for manual editing. The algorithm independently analyzes user strokes, computes optimal framing decisions, and generates the output video without human intervention, achieving both high content quality and efficiency.
Solution Approach 2:
The system replaces manual mechanical editing operations with an automated computational optimization process. Instead of requiring editors to manually adjust frames to preserve user strokes, the cost function-driven algorithm automatically computes and applies the optimal transformations, dramatically reducing editing time while maintaining or improving content quality.
4Productivity
If automated reframing is performed without considering user strokes, then processing speed is maintained, but user experience deteriorates
Solution Approach 1:
The system performs preliminary analysis of user strokes and salient information before the actual reframing operation. This pre-processing step enables the automated system to understand what content is important and plan the transformation accordingly, ensuring good user experience without requiring slow manual review and adjustment during the main processing phase.
Solution Approach 2:
The cost function provides continuous feedback during the automated reframing process, guiding the optimization to preserve user experience-critical elements. This feedback mechanism allows the system to make intelligent decisions about framing and cropping that prioritize user experience, all while maintaining automated processing speed and efficiency.
Data Source
AI summary
Embodiments of the present disclosure include obtaining an input video depicting a change to an image, wherein the input video has a first aspect ratio. Some embodiments compute a cost function for a frame of the input video based on a location of the change. A modified frame corresponding to the frame of the input video is generated based on the cost function. In some examples, the modified frame has a second aspect ratio different from the first aspect ratio. Then, an output video including the modified frame is generated and the output video has the second aspect ratio.