3D Image Reconstruction via User-Defined Region Selection
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Solution Overview
Problem
Three-dimensional image reconstruction on portable devices like smartphones and tablets is hindered by high computational load and limited processing power, exacerbated by imprecise user interaction on small screens.
Innovation Solution
A system that allows users to specify areas of interest within an image, detect and track features across multiple frames, and perform 3D reconstruction by constructing and combining planar elements, reducing the number of features to be processed through user-defined plane and region selections.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple images are processed to reduce point cloud uncertainty, then measurement precision is improved, but device complexity and processing load increase
Solution Approach 1:
The patent segments the image processing task by dividing the image into multiple tiles or regions. Each tile is processed independently to generate a point cloud, which are then merged to form the complete 3D reconstruction. This segmentation reduces the computational complexity of processing the entire image at once while maintaining measurement precision through systematic coverage of all regions.
Solution Approach 2:
The patent implements progressive refinement where processing starts with a subset of images or regions and gradually incorporates additional data. The system performs initial 3D reconstruction with limited data and iteratively refines the model by incorporating more images or adjusting parameters, allowing the device to manage processing load while progressively improving measurement precision.
2Measurement precision
If feature tracking is performed across multiple image frames, then three-dimensional reconstruction accuracy is improved, but use of energy and processing time increase
Solution Approach 1:
The patent performs preliminary feature detection and matching before full 3D reconstruction. Key features are identified and tracked across frames in advance, creating a foundation for subsequent reconstruction. This preliminary action reduces the computational energy required during the main reconstruction process while maintaining accuracy through pre-established feature correspondences.
Solution Approach 2:
The patent extracts and focuses processing on salient features that contribute most to reconstruction accuracy. By identifying and isolating key features from the full image data, the system performs tracking only on these critical elements rather than all pixels or features, significantly reducing energy consumption while preserving reconstruction accuracy.
3Productivity
If user interface allows precise area selection, then processing load is reduced, but ease of operation decreases
Solution Approach 1:
The patent implements temporary or provisional selection modes where users can make quick, approximate selections without committing to precise boundaries immediately. The system allows users to select regions of interest with simple gestures and then refines the selection automatically or through subsequent adjustments, reducing the operational complexity while maintaining processing efficiency by focusing on user-indicated areas.
Data Source
AI summary
Improved mechanisms for three-dimensional image reconstruction are disclosed. A user is presented with a scene image and allowed to select elements of the image, such as planes, within which features are to be detected. The features are detected and tracked and objects (such as planes) are constructed. The user is allowed to revise the constructed objects and may be allowed to repeat image element selection, with feature detection and tracking and object construction being repeated. When element selection and object construction and user revision are completed, a three-dimensional reconstruction of the scene image is computed.