Corruption Detection for 3D Environment Reconstruction
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Solution Overview
Problem
Current 3D reconstruction algorithms face challenges in accurately estimating camera locations and orientations due to corrupted data, leading to inaccurate reconstruction of three-dimensional environments, especially when dealing with outlier measurements.
Innovation Solution
A system that calculates inconsistency scores for predicted pairwise directions using an iteratively reweighted weight statistic to detect and remove corrupted data, improving the accuracy of camera location estimation and 3D reconstruction by filtering out unreliable image sets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional 3D reconstruction algorithms are used, then the reconstruction process can be completed, but the accuracy is degraded due to corrupted data and outlier measurements
Solution Approach 1:
The patent applies preliminary action by computing inconsistency scores for all pairwise direction measurements before performing the main 3D reconstruction. This preprocessing step identifies and flags corrupted measurements in advance, allowing the reconstruction algorithm to exclude them and achieve higher accuracy without compromising reliability.
Solution Approach 2:
The patent converts the harmful effect of corrupted data into a benefit by using the inconsistency of corrupted pairwise directions as a detectable signal. The method computes inconsistency scores that highlight corrupted measurements, transforming the harm of outliers into useful information for filtering, thereby improving both measurement precision and robustness.
2Measurement precision
If outlier detection algorithms are applied as preprocessing, then measurement precision improves, but device complexity and computational overhead increase
Solution Approach 1:
The patent replaces complex mechanical outlier detection systems with a simpler computational approach based on cycle consistency checks. Instead of using sophisticated statistical methods or multiple preprocessing stages, the invention uses the geometric property that pairwise directions around a cycle should sum to zero, providing a computationally efficient mechanism to identify corrupted data.
Solution Approach 2:
The patent changes the parameter being measured from general data quality metrics to a specific geometric inconsistency parameter. By focusing on the sum of pairwise directions around cycles, the method transforms the complex problem of outlier detection into a straightforward parameter comparison, reducing algorithmic complexity while maintaining precision.
3Measurement precision
If more images are processed to improve reconstruction quality, then measurement precision increases, but loss of time and computational resources increases
Solution Approach 1:
The patent extracts and removes corrupted image sets from the processing pipeline using inconsistency score thresholds. By identifying and excluding only the problematic measurements rather than processing all images uniformly, the method maintains high reconstruction accuracy from valid data while reducing the time and computational resources wasted on corrupted inputs.
Data Source
AI summary
In general, a system is described that includes a set of one or more cameras and a computing device. The computing device receives a plurality of images of a three-dimensional environment captured by the one or more cameras, and a respective camera that captures a respective image is distinctly positioned at a respective particular location and in a respective particular direction. The computing device generates a plurality of image sets that each include at least three images. For each image set, the computing device calculates a plurality of predicted pairwise directions. The computing device compares a first sum of model pairwise directions with a second sum of the plurality of predicted pairwise directions and generates an inconsistency score for the respective image set. The computing device then reconstructs a digital representation of the three-dimensional environment depicted in the images.