3D Model Generation Excluding Blurry Image Regions
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Solution Overview
Problem
The construction of a three-dimensional model from a series of two-dimensional images is time-consuming, computationally expensive, and often results in inaccurate models due to the combination of images with varying clarity and focus.
Innovation Solution
A method that identifies and excludes image regions with undesirable attributes, such as blurriness or lack of focus, from the generation process, using pre-processing techniques to improve accuracy and speed by ignoring misleading pixels and utilizing more clear views from other images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If all regions of source images are used to generate three-dimensional model, then more data is available for model construction, but processing time increases and accuracy decreases due to inclusion of blurry or unfocused regions
Solution Approach 1:
The patent divides the source images into multiple regions of interest based on focus quality assessment. Each region is evaluated independently for sharpness and clarity, allowing selective processing of only the useful portions of each image. This segmentation approach prevents processing of blurry or unfocused regions, thereby reducing processing time while maintaining model accuracy.
Solution Approach 2:
The patent applies different processing treatments to different regions of the source images based on their local quality characteristics. Regions with good focus and clarity are selected for three-dimensional model construction, while regions with blurriness or poor focus are excluded. This local quality assessment ensures that only high-quality data contributes to the final model, improving accuracy without requiring processing of entire images.
2Reliability
If all source images are processed completely, then comprehensive data is captured, but computational resources and processing time are excessively consumed
Solution Approach 1:
The patent performs preliminary assessment of source images before the main three-dimensional model construction process. Focus quality metrics are calculated and regions are pre-selected or pre-rejected based on their suitability for model building. This preliminary action filters out poor-quality regions beforehand, ensuring that only reliable data enters the computationally intensive model generation phase, thereby improving both reliability and productivity.
Solution Approach 2:
The patent applies partial processing to source images by selectively processing only the portions that meet quality criteria. Instead of processing entire images uniformly, the system identifies and processes only the in-focus, high-quality regions that contribute meaningfully to model reliability. This partial action approach maintains model reliability while significantly reducing the computational burden and improving generation speed.
3Quantity of substance
If regions with varying clarity are combined in model generation, then more image data is utilized, but the resulting three-dimensional model becomes less accurate
Solution Approach 1:
The patent evaluates each region of source images for its local quality characteristics, specifically focus sharpness and clarity. Regions are classified based on their quality metrics, and only those meeting predetermined thresholds are selected for inclusion in the three-dimensional model construction. This ensures that high-precision regions contribute to the model while low-precision blurry regions are excluded, maintaining model precision while utilizing sufficient data quantity from quality regions.
Data Source
AI summary
Methods, systems, and computer readable media related to generating a three-dimensional model of a target object. A first source image, of a plurality of source images of a target object, is analyzed to identify a first region of the first image, the first region having attributes meeting one or more pre-defined criteria. The first region is marked for exclusion from use in generating a three-dimensional model of the target object. The three-dimensional model of the target object is generated using the plurality of source images. The marked first region is excluded in the generation of the three-dimensional model.