Virtual Subject Superimposition With Scene-Aware Environmental Matching
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Solution Overview
Problem
Existing image processing techniques fail to accurately reflect real weather and terrain information on virtual subjects superimposed on captured images, leading to unnatural superimposed images.
Innovation Solution
An image processing apparatus and method that acquires scene information, generates and processes virtual subjects based on environmental and spatial information using learning models, and superimposes them onto captured images to align with real conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a virtual subject is simply superimposed on a captured image, then the superimposition process is simple and fast, but the lighting conditions and environmental consistency are unnatural
Solution Approach 1:
The system performs preliminary analysis of the captured image to detect lighting conditions, weather, and terrain information before superimposing the virtual subject. This allows the virtual subject to be pre-adjusted with appropriate lighting, shadows, and environmental effects, ensuring natural consistency without complex real-time processing during superimposition.
Solution Approach 2:
The system changes multiple parameters of the virtual subject including lighting direction, intensity, color temperature, weather effects (rain, snow, wind), and terrain interaction based on the analyzed scene information. These parameter adjustments make the virtual subject consistent with the real environment while maintaining efficient superimposition.
2Manufacturing precision
If real lighting information is reflected on the virtual subject, then lighting consistency improves, but weather and terrain information are still not reflected
Solution Approach 1:
The system creates a multi-functional processing framework that simultaneously handles multiple types of environmental information including lighting conditions, weather effects (rain, snow, wind, fog), and terrain characteristics. This universal approach ensures all environmental factors are reflected on the virtual subject comprehensively, not just lighting.
Solution Approach 2:
The system segments environmental information into distinct categories (lighting, weather, terrain) and processes each category separately with specialized algorithms. This segmentation allows comprehensive environmental coverage while maintaining organized and efficient processing of each environmental factor.
3Manufacturing precision
If comprehensive scene information is processed to reflect all environmental factors, then naturalness of superimposed image improves, but processing complexity increases
Solution Approach 1:
The system performs preliminary detection and analysis of all environmental factors (lighting, weather, terrain) from the captured image before virtual subject generation. This preliminary action organizes scene information in advance, allowing complex environmental processing to be broken down into manageable steps that maintain naturalness without overwhelming processing complexity.
Solution Approach 2:
The system creates simplified digital representations (copies) of environmental information from the captured image, such as extracting lighting direction and intensity, weather conditions, and terrain features. These copied environmental parameters are then applied to the virtual subject, achieving high naturalness through efficient data replication rather than complex real-time processing.
Data Source
AI summary
An image processing apparatus comprises: an acquisition unit that acquires scene information of a scene being captured by an image capturing unit; a generation unit that generates a virtual subject; a processing unit that processes the virtual subject based on the scene information; and a superimposing unit that superimposes the virtual subject processed by the processing unit onto image data of the scene obtained from the image capturing unit.