Digital Image Subdivision for 3D Modeling Accuracy
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Solution Overview
Problem
Processing high-resolution digital images for 3D modeling is computationally expensive and often infeasible due to memory constraints, leading to reduced quality when images are down-sampled, and existing methods fail to efficiently handle distortions and identify relevant sub-images for accurate 3D reconstruction.
Innovation Solution
The method involves subdividing digital images into smaller sub-images that maintain the original spatial resolution, associating each with synthesized camera parameters, and applying distortion corrections, allowing for efficient processing and identification of relevant sub-images for 3D modeling, thereby reducing computational resources and improving accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-resolution digital images are processed for 3D modeling, then 3D model accuracy is improved, but computational cost and memory consumption increase significantly
Solution Approach 1:
The patent divides high-resolution digital images into multiple smaller sub-images while preserving the original spatial resolution. This segmentation allows the system to process image data in manageable chunks, reducing memory consumption and computational cost while maintaining the ability to generate accurate 3D models through photogrammetry processing of the sub-images.
2Use of energy by moving object
If digital images are down-sampled to reduce memory consumption, then processing becomes feasible, but 3D model accuracy deteriorates
Solution Approach 1:
Instead of down-sampling the entire image, the system segments the high-resolution image into smaller sub-images that maintain the original spatial resolution. This allows the system to work with smaller data volumes in memory while preserving the detail needed for accurate 3D reconstruction.
Solution Approach 2:
The patent transitions from processing a single large image to processing multiple smaller sub-images, changing the dimensional approach from one large dataset to multiple smaller datasets. This maintains information content while reducing individual processing unit size for better memory management.
3Measurement precision
If distortion correction is applied to digital images, then 3D modeling accuracy is improved, but processing time and computational cost increase
Solution Approach 1:
The patent applies distortion correction to individual sub-images rather than to entire high-resolution images. This segmentation approach reduces the computational burden and processing time for distortion correction while still achieving accurate 3D modeling results through the processed sub-images.
Data Source
AI summary
Digital image processing methods performed by a computer are disclosed. In one example, a first digital image captured by a real camera is sub-divided into a first plurality of sub-images. A second digital image captured by a real camera is sub-divided into a second plurality of sub-images. A set of image features in a first sub-image of the first plurality of sub-images is identified. A subset of neighboring sub-images is identified from the second plurality of sub-images based at least on each neighboring sub-image of the subset of neighboring sub-images having one or more corresponding image features in common with the set of image features identified in the first sub-image.