Photo Pre-Edit System Using Object Detection and Filter Parameter Selection
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Solution Overview
Problem
Current image editing systems lack the ability to automatically adjust filter parameters based on the content of photos, leading to suboptimal editing results as users must manually select and apply filters without considering the specific objects or contexts within the images.
Innovation Solution
A method that detects and classifies objects in photos, selecting and adjusting filter parameters based on recognized objects such as people, faces, indoor, and outdoor elements, allowing for automatic pre-edits that enhance image quality by applying filters with optimized settings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual filter selection is used, then user control over editing is maintained, but editing efficiency and quality are reduced due to lack of content-aware adjustments
Solution Approach 1:
The system performs automatic object detection and filter parameter selection without requiring manual user input. The computing device autonomously analyzes photo content, identifies objects, and adjusts filter parameters based on detected objects, enabling the editing system to serve itself rather than requiring continuous user guidance.
Solution Approach 2:
The system dynamically changes filter parameters based on detected objects in the photo. Different objects trigger different parameter adjustments, allowing the same filter type to adapt its parameters automatically according to the photo content, thereby improving editing efficiency and quality simultaneously.
2Manufacturing precision
If generic filters are applied to all photos, then simplicity is maintained, but editing quality deteriorates due to lack of content-specific optimization
Solution Approach 1:
The system applies different filter parameters to different regions or objects within the same photo based on local content analysis. Each detected object receives customized parameter adjustments tailored to its specific characteristics, achieving high editing precision without requiring the user to manually configure complex settings for each element.
Solution Approach 2:
The system performs preliminary object detection and analysis before applying filters, pre-determining the appropriate parameters based on detected objects. This preliminary action enables content-specific optimization to be automatically prepared and applied, maintaining simplicity while achieving high editing precision.
3Adaptability or versatility
If automatic object detection is implemented, then content-aware editing is enabled, but processing time increases
Solution Approach 1:
The system performs partial object detection by focusing on identifying only the key objects necessary for filter selection rather than analyzing every detail in the photo. This selective approach enables content-aware filtering to be applied without requiring complete and exhaustive object detection, thereby reducing processing time while maintaining adaptability.
Data Source
AI summary
Implementations generally relate to providing pre-edits to photos. In some implementations, a method includes detecting one or more objects in a photo. The method further includes classifying the one or more objects. The method further includes selecting one or more parameter values for one or more respective filters based on the classifying of the one or more objects.