3D Model Color Patch Selection for Seamless Scanning
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Solution Overview
Problem
Current handheld scanning technologies face challenges in generating high-quality three-dimensional models due to device constraints, user movement, and variations in light and camera position, leading to poor color fidelity and visible seams in the models.
Innovation Solution
A method for assigning colors to points in a 3D model by analyzing localized patches of pixels, determining quality and smoothness scores, and selecting representative patches to minimize the number of images used, thereby improving color accuracy and reducing seams.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If handheld scanning technology is used to capture color images for 3D models, then the scanning process becomes portable and accessible, but the quality of color images deteriorates due to device constraints, user movement, and lighting variations
Solution Approach 1:
The patent divides the image selection process into localized patch-level evaluations rather than evaluating entire images. Each patch is independently assessed for quality metrics (blur, noise, lighting), allowing the system to select the best patch from multiple images for each region of the 3D model. This segmentation approach resolves the contradiction by enabling portable scanning while maintaining color accuracy through localized quality assessment.
Solution Approach 2:
The patent applies different quality criteria and selection strategies to different regions of the 3D model based on local image characteristics. Each patch is evaluated according to its specific quality metrics, and the best patch is selected for each local region. This local quality approach allows the system to tolerate variations in overall image quality while ensuring high color fidelity in each localized area, thus resolving the portability versus quality contradiction.
2Measurement precision
If multiple color images are used to determine colors for points in the 3D model, then color accuracy may improve through averaging, but visible seams and artifacts increase due to inconsistencies between images
Solution Approach 1:
The patent segments the color determination process into independent patch-level decisions. Instead of averaging colors across multiple images for each point (which causes seams), the system evaluates each patch individually and selects the single best patch for each region. This segmentation eliminates seams by ensuring consistent color selection within each localized area while maintaining overall color accuracy.
Solution Approach 2:
The patent inverts the traditional approach by not selecting one best image for the entire model or averaging across multiple images. Instead, it inverts the selection to the patch level, choosing the best patch for each local region from multiple images. This inverted approach at the patch level simultaneously achieves color accuracy and seamlessness, resolving the contradiction between these two features.
3Productivity
If the scanning device is moved quickly to improve scanning speed, then productivity increases, but image quality deteriorates due to motion blur and camera position fluctuations
Solution Approach 1:
The patent segments the evaluation of image quality into multiple independent quality metrics (blur, noise, lighting, focus) assessed at the patch level. This segmentation allows the system to quickly evaluate multiple images captured during fast scanning and selectively use only the high-quality patches, thus maintaining color accuracy despite fast scanning speeds that produce mixed quality images.
Solution Approach 2:
The patent changes the evaluation parameter from overall image quality to localized patch quality with multiple specific metrics. By evaluating patches based on specific parameters (blur level, noise, lighting conditions) rather than overall image quality, the system can identify and select high-quality patches even from images captured during fast movement, thus maintaining color accuracy while enabling fast scanning.
Data Source
AI summary
The disclosure describes systems and methods of selecting colors to points in a digital three-dimensional (3D) model representing a scanned object, based on points and color images associated with the 3D model. Certain embodiments involve selecting from the images a patch for each point in the 3D model, and determining a quality of the patches. The selected patches are analyzed to determine an overall score, representing aggregated quality of the patches and an aggregated smoothness indicating variation between patches selected for neighboring points. In some examples, multiple sets of selected patches are analyzed and scored, and the scores are compared to determine a representative patch set that optimizes the quality and the smoothness. Colors are assigned to the points of the digital model based on the representative set of patches.