Predicted Background Image Generation for Object Detection
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Solution Overview
Problem
Existing methods for generating predicted background images for object detection fail to maintain uniform light source environments, leading to inaccurate object detection, especially in outdoor settings where light source conditions change.
Innovation Solution
The method generates a small region panorama image group with overlapping regions, allowing for the creation of a predicted background image with a consistent light source environment, using linearization processing to match the target image's light source conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a predicted background image is synthesized from multiple shot images with different light source environments, then the coverage area and adaptability are improved, but the uniformity of light source environment deteriorates
Solution Approach 1:
The patent segments the panorama image into multiple small region images, each captured under different light source environments. By processing and selecting appropriate regions from these segmented images, the system can generate a predicted background image that matches the light source environment of the detection target image, thus resolving the contradiction between adaptability and uniformity.
Solution Approach 2:
The patent applies local quality by allowing different regions of the predicted background image to be sourced from different small region images, each with its own light source characteristics. This enables the predicted background image to have locally appropriate light source environments that match the corresponding regions of the detection target image.
2Productivity
If background difference is performed using a predicted background image with non-uniform light source environment, then the processing speed is maintained, but the detection accuracy deteriorates due to intensity differences
Solution Approach 1:
The patent changes the light source environment parameter of the predicted background image by selecting and processing small region images with matching light source characteristics. This parameter matching eliminates intensity differences between the predicted background image and detection target image, thereby improving detection accuracy while maintaining processing efficiency.
3Adaptability or versatility
If light source environment changes after synthesis of predicted background image, then the adaptability to changing conditions is improved, but the consistency between detection target image and predicted background image deteriorates
Solution Approach 1:
The patent performs preliminary action by capturing multiple small region images under different light source environments before the actual detection. When the detection target image is acquired, the system selects and processes the appropriate pre-captured small region image that matches the current light source environment, thereby maintaining consistency despite environmental changes.
Solution Approach 2:
The patent introduces dynamics by making the predicted background image adaptable to changing light source environments. The system dynamically selects and processes small region images based on the light source conditions of the detection target image, allowing the predicted background image to change according to environmental conditions while maintaining consistency.
Data Source
AI summary
A small region panorama image group (I1P, I2P, I3P) is generated in advance. The small region panorama image group (I1P, I2P, I3P) includes images including a common shooting range, being composed of a plurality of common partially overlapped regions (A, B, C, D), and having independency from each other in each partially overlapped region (A, B, C, D). With the use of the small region panorama image group (I1P, I2P, I3P), a predicted background image is generated in which light source environment is the same as that of a shot target image.


