Media Editing System Depth-Based Foreground Background Effect Application
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Solution Overview
Problem
Existing media editing tools are tedious and time-consuming for users to manually apply effects to digital content, as they lack automation in distinguishing and processing foreground and background regions based on depth information.
Innovation Solution
A media editing system that determines depth information in digital images, separates them into foreground and background regions, and automatically applies specific effects to each region using a processor-based application with a depth analyzer, region parser, effect selector, and image editor.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If manual editing is used to apply effects to digital content, then users can achieve desired effects, but the editing process becomes tedious and time-consuming
Solution Approach 1:
The system performs automatic depth estimation, foreground-background segmentation, and effect application without requiring manual user intervention. The media editing apparatus autonomously analyzes the digital image, determines depth information, separates regions, and applies appropriate effects, making the editing process self-executing rather than manually controlled.
Solution Approach 2:
The system performs preliminary depth estimation and region segmentation before effect application. By pre-processing the image to identify foreground and background regions based on depth information, the system prepares the edited content in advance, enabling rapid effect application without time-consuming manual region selection.
2Productivity
If automated effect application is implemented, then editing efficiency is improved, but the system complexity increases due to depth analysis and region segmentation requirements
Solution Approach 1:
The system replaces manual mechanical editing operations with automated computational processes. Instead of requiring users to manually select regions and apply effects, the system uses depth estimation algorithms and automated segmentation to perform these tasks computationally, substituting human manual operations with automated digital processing.
Solution Approach 2:
The media editing apparatus integrates multiple functions including depth estimation, region segmentation, effect selection, and effect application into a single unified system. This multi-functional approach consolidates what would otherwise require separate tools and processes, managing system complexity through integration while maintaining high editing efficiency.
3Extent of automation
If depth information processing is added to distinguish foreground and background, then automated region-based editing is enabled, but the processing time and computational requirements increase
Solution Approach 1:
The system applies depth estimation and region segmentation only to the extent necessary for effective effect application. Rather than performing exhaustive analysis of all image regions, the system focuses computational resources on identifying key foreground-background boundaries and applying effects selectively to relevant regions, reducing unnecessary processing time.
Data Source
AI summary
Disclosed are systems and methods for automatically applying special effects based on media content characteristics. A digital image is obtained and depth information in the digital image is determined. A foreground region and a background region in the digital image are identified based on the depth information. First and second effects are selected from a grouping of effects, where the first effect is applied to at least a portion of the foreground region and the second effect is applied to at least a portion of the background region.