Automatic Video Cropping for Aesthetic Mobile Display Framing
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Solution Overview
Problem
Amateur users often capture video content without regard to composition, framing, or camera movement, resulting in jarring or confusing content, and determining a desirable cropping presentation imposes a cognitive burden and leads to unnecessary power consumption.
Innovation Solution
Automate the processing and presentation of video content by implementing a method for automatic cropping on electronic devices, such as mobile phones and tablets, using touch-sensitive surfaces to enhance aesthetic appeal.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If manual cropping determination is performed by users, then cropping precision can be controlled, but cognitive burden and time commitment increase substantially
Solution Approach 1:
The system automatically determines and applies cropping parameters without requiring user intervention or manual adjustment. The processing system analyzes video content and autonomously selects optimal cropping regions, eliminating the cognitive burden of manual determination while maintaining acceptable cropping precision through automated algorithms.
Solution Approach 2:
The patent replaces manual mechanical cropping determination with automated computational processing. Instead of users manually selecting crop regions through interfaces, the system uses image processing algorithms and machine learning models to automatically identify and apply appropriate cropping parameters.
2Manufacturing precision
If manual cropping determination is performed by users, then cropping precision can be controlled, but time commitment increases substantially
Solution Approach 1:
The system performs cropping determination in advance during video processing, rather than requiring users to manually analyze and select crop regions after capture. The automated system pre-processes video content to identify optimal cropping parameters, significantly reducing the time users would need to spend on manual analysis and adjustment.
Solution Approach 2:
The patent replaces time-consuming manual cropping determination with automated computational processing. The system uses image processing algorithms and machine learning models to rapidly analyze video content and determine optimal cropping parameters, reducing time commitment from minutes or hours of manual analysis to seconds of automated processing.
3Ease of operation
If automated cropping processing is implemented, then ease of operation improves, but device complexity increases
Solution Approach 1:
The processing system integrates multiple functions into a unified automated cropping pipeline, including video analysis, subject detection, cropping parameter determination, and output generation. By consolidating these functions into a single multi-functional processing system, the patent manages complexity through integration rather than multiplication of separate components.
Solution Approach 2:
The system dynamically adjusts processing parameters based on video content characteristics, such as changing cropping regions, zoom levels, and processing intensity according to detected subjects and scene complexity. This adaptive parameter adjustment allows the system to handle diverse video content efficiently while managing computational complexity through intelligent parameter selection.
Data Source
AI summary
Electronic devices are often equipped with a camera for capturing video content and/or a display for displaying video content. However, amateur users often capture video content without regard to composition, framing, or camera movement, resulting in video content that can be jarring or confusing to viewers. There is a need to automate the processing and presentation of video content in an aesthetically pleasing manner. The embodiments described herein provide a method of automatically cropping video content for presentation on a display.