3D Reconstruction Pose Optimization with Neural Error Correction
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Solution Overview
Problem
Existing high-precision three-dimensional reconstruction technologies are limited by high costs and complexity, making them unsuitable for widespread use in virtual reality applications due to the need for large sensor arrays and significant computing power, and suffer from reconstruction errors caused by sensor measurement inaccuracies and image data quality issues.
Innovation Solution
A method combining local pose optimization, neural network prediction, global pose optimization, and neural network completion to achieve high-quality and high-precision three-dimensional reconstruction, reducing the need for extensive sensor arrays by using a hierarchical reconstruction strategy that includes local and global optimization steps.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If high-precision three-dimensional reconstruction is achieved using complex sensor devices and computing devices, then manufacturing precision is improved, but device complexity increases
Solution Approach 1:
The patent divides the three-dimensional reconstruction process into multiple stages: initial model construction from sparse views, iterative refinement stages, and final optimization. Each stage processes a subset of images and progressively improves the model, avoiding the need to process all images simultaneously as in traditional methods.
Solution Approach 2:
The patent performs preliminary construction of an initial three-dimensional model using only a subset of images before the main reconstruction process. This preliminary model serves as a foundation that guides subsequent refinement stages, enabling accurate reconstruction with fewer images.
2Manufacturing precision
If high-precision three-dimensional reconstruction is achieved using complex sensor devices and computing devices, then manufacturing precision is improved, but ease of manufacture deteriorates
Solution Approach 1:
The patent segments the large-scale reconstruction problem into smaller, manageable stages that can be implemented with consumer-grade sensors. The multi-stage process breaks down the computational burden and allows incremental implementation without requiring complex hardware systems.
3Ease of operation
If consumer-grade sensors are used for three-dimensional reconstruction, then ease of operation is improved, but measurement precision deteriorates
Solution Approach 1:
The patent performs preliminary construction of an initial three-dimensional model using a subset of images captured by consumer-grade sensors. This preliminary model captures the essential geometry and provides a foundation for subsequent refinement, enabling accurate reconstruction despite sensor limitations.
Solution Approach 2:
The patent implements iterative refinement where the three-dimensional model is continuously updated and refined based on feedback from multiple image views. Each refinement stage uses the previous model as a starting point and progressively improves accuracy by incorporating additional constraints and information from the image set.
Data Source
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AI summary
The present application discloses a three-dimensional reconstruction method, comprising: performing local pose optimization by using a target image frame to obtain a local pose error; performing neural network prediction on the target image frame to obtain an initial reconstruction error; performing three-dimensional reconstruction according to the local pose error and the initial reconstruction error to obtain an initial reconstruction model; performing global pose optimization by using historical image frames to obtain a global optimization result and a global pose error; performing neural network completion on the global optimization result to obtain a final reconstruction error; and optimizing the initial reconstruction model according to the global pose error and the final reconstruction error to obtain a final reconstruction model. The three-dimensional reconstruction method can achieve high-quality and high-precision three-dimensional reconstruction more quickly and conveniently. The present application further discloses a three-dimensional reconstruction apparatus and system, and a computer readable storage medium, which all have the above-mentioned beneficial effects.