3D Model Building Using Registration Energy Minimization
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Solution Overview
Problem
Existing methods for building three-dimensional models from two-dimensional images using a single camera often fail due to calculation deviations in determining rotation angles and moving distances, leading to inaccuracies in integrating 3D point clouds and resulting in a 3D model that differs significantly from the physical object.
Innovation Solution
A method that converts depth information from images into 3D point clouds, determines motion parameters to establish an optimal camera path, and integrates 3D point clouds along this path to minimize registration energy estimates, ensuring accurate integration and construction of a 3D model.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If 3D point clouds are integrated in real-time as images are captured, then the process is efficient and continuous, but calculation deviations accumulate and cannot be corrected, leading to inaccurate 3D models
Solution Approach 1:
The patent performs preliminary actions by first determining motion parameters and calculating registration energy estimates before actually integrating the 3D point clouds. This allows the system to identify and correct calculation deviations in advance, preventing accumulation of errors while maintaining efficient processing. The optimal camera path is determined beforehand based on minimizing registration energy, ensuring accuracy is achieved without sacrificing productivity.
2Ease of manufacture
If motion parameters are determined sequentially for each image, then the process is simple and straightforward, but any calculation deviation causes integration failure and cannot be corrected
Solution Approach 1:
The patent introduces feedback mechanisms by calculating registration energy estimates for each image's 3D point cloud integration and using this information to determine the optimal camera path. The system monitors registration quality and can identify when calculation deviations occur, allowing for real-time correction and ensuring reliable integration success even when simple sequential processing is used.
3Duration of action of moving object
If depth information is converted to 3D point clouds immediately, then the 3D model building process is continuous, but integration errors accumulate and cause the final model to differ significantly from the physical object
Solution Approach 1:
The patent applies preliminary action by determining motion parameters and optimizing the camera path before integrating 3D point clouds. This allows the system to maintain continuous processing while preventing error accumulation. The registration energy estimate calculation is performed in advance to identify optimal integration paths, ensuring high fidelity 3D models are achieved through proactive error prevention rather than reactive correction.
Data Source
AI summary
A method to build a 3D model for a physical object includes the following steps. First, depth information of a plurality of images is converted into a plurality of 3D point clouds. Then, the motion parameters of the camera to gather each image relative to a previous image are determined according to the 3D point clouds. Next, a registration energy estimate value of each image's 3D point cloud, as being integrated into a previous image's 3D point cloud, is determined according to corresponding motion parameters. Then, the motion parameters are varied to minimize the estimate value. An optimal camera path is determined according to the varied motion parameters. Finally, a 3D model of the physical object is built according the optimal camera path.