Depth Estimation Model Training Using Multi-View Consistency
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Solution Overview
Problem
Current methods for estimating depth information from two-dimensional images are limited in accuracy and consistency, particularly when dealing with images captured at different angles.
Innovation Solution
A training method and device that generate per-pixel depth errors by obtaining and processing depth information from multiple images and camera parameters, using coordinate system transformations and consistency verification to improve the accuracy of depth estimation models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If depth information is estimated from a single 2D image, then the process is simple and fast, but the accuracy and consistency of depth estimation deteriorates
Solution Approach 1:
The patent transitions from single-image 2D depth estimation to multi-image 3D depth estimation by capturing images from multiple viewpoints and performing coordinate system transformations between different image coordinate systems and 3D space, thereby improving depth accuracy through additional spatial dimensions
Solution Approach 2:
The patent introduces 3D space as an intermediary coordinate system to transform and reconcile depth information from multiple 2D images captured at different angles, enabling accurate depth estimation by finding consistent 3D coordinates that satisfy all viewpoint constraints
2Measurement precision
If multiple images from different angles are used for depth estimation, then depth accuracy improves, but the complexity of processing and coordinate transformation increases
Solution Approach 1:
The patent divides the depth estimation process into separate processing stages for each image, where each image is independently transformed to 3D space and then integrated, allowing modular processing that reduces overall complexity despite handling multiple images
Solution Approach 2:
The patent transforms depth estimation from pixel-space operations to 3D coordinate-space operations by changing the parameter domain, enabling more accurate and systematic handling of multi-view geometry through camera parameters and coordinate transformations
Data Source
AI summary
A training method and device for estimating depth information of an image are disclosed. The training method may include obtaining depth information of a first image according to a resolution based on the first image, and outputting a per-pixel depth error of the first image based on the depth information of the first image, depth information of a second image, and camera parameters.