Scene Reconstruction Using Characteristic Region Extraction
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Solution Overview
Problem
The existing methods for reconstructing scenes from large collections of images are inefficient due to the need for manual removal of irregular and useless images, leading to high manpower costs and exponential increase in reconstruction time with increasing data volume.
Innovation Solution
A method and apparatus that acquire a first image set, extract and recognize characteristic regions using algorithms, and perform three-dimensional reconstruction only on scene characteristic regions, filtering out useless regions to improve efficiency and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual removal of irregular and useless images is performed, then image quality is improved, but manpower costs increase
Solution Approach 1:
The system performs automatic image filtering and characteristic region extraction without human intervention. The computer executes algorithms to identify and remove irregular images, and automatically extracts characteristic regions from valid images, making the system self-servicing and eliminating manual labor while maintaining image quality
Solution Approach 2:
The patent replaces manual mechanical operations with automated computational systems. Instead of human operators manually reviewing and filtering images, the system uses computer-based image processing algorithms and machine learning models to automatically identify irregular images and extract characteristic regions, substituting mechanical human labor with automated digital processing
2Loss of information
If full image data is used for reconstruction, then completeness is improved, but reconstruction time increases exponentially
Solution Approach 1:
The patent extracts only the essential characteristic regions from images rather than processing complete image data. By identifying and isolating key characteristic regions that contain the most important scene information, the system reduces the data volume required for reconstruction while maintaining completeness of the reconstructed scene
Solution Approach 2:
The patent segments images into characteristic regions and non-characteristic regions, processing only the relevant segments for reconstruction. This segmentation approach divides the large-scale image data into manageable characteristic region components, reducing computational complexity and reconstruction time while preserving essential scene information
Data Source
AI summary
A scene reconstruction method, apparatus, terminal device, and storage medium. The method includes: acquiring a first image set matching a to-be-reconstructed scene (11); extracting a characteristic region of an image in the first image set by using a characteristic extraction algorithm (12); performing recognition on the characteristic region to obtain a scene characteristic region in the image (13); and performing three-dimensional reconstruction on the to-be-reconstructed scene according to the scene characteristic region in the image, and rendering and generating the to-be-reconstructed scene (14). Some useless and unstable characteristic regions are filtered off, and the three-dimensional reconstruction on the to-be-reconstructed scene is performed only according to the scene characteristic region associated with the to-be-reconstructed scene, thereby improving the efficiency and accuracy of reconstruction.