Multi-Camera Shape Estimation for Occlusion-Safe 3D Models
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Solution Overview
Problem
Existing methods for generating three-dimensional shape models are inaccurate due to the inability to correctly select cameras that can capture elements of the object without obstacles, leading to insufficient model accuracy.
Innovation Solution
A shape estimation apparatus that uses multiple image capturing apparatuses to estimate a three-dimensional shape, determines which elements to delete based on color variance and distance thresholds, and generates a refined element group by excluding elements that are not visible or have significant color variance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If elements are deleted from the shape model based on color variance using multiple cameras, then the accuracy of the shape model is improved, but elements in concave or thin regions may be erroneously deleted
Solution Approach 1:
The patent applies local quality by differentiating the treatment of elements based on their spatial characteristics. Elements are categorized into two groups: those where color variance indicates occlusion (deletable) and those where color variance is unreliable (non-deletable). This local differentiation ensures that deletion decisions are made based on the specific properties of each element's region, preventing erroneous deletions in concave or thin regions while maintaining accuracy improvement in other areas.
2Measurement precision
If a mesh is used to represent the shape model, then the three-dimensional shape can be accurately represented, but the complexity of processing and storing the model increases
Solution Approach 1:
The patent extracts and removes unnecessary elements from the mesh model based on occlusion analysis. By identifying and deleting elements that are occluded from the camera's viewpoint (determined through the straight-line intersection test), the model is simplified while maintaining the accuracy of visible surfaces. This extraction process reduces model complexity and processing requirements without sacrificing the fidelity of the representable shape.
Data Source
AI summary
A shape estimation apparatus estimates, based on captured images obtained by capturing an object from different directions using a plurality of image capturing apparatuses, a first element group representing a three-dimensional shape of the object, determines whether to delete elements from the first element group, and generates a second element group by deleting the elements from the first element group. With respect to a first element among elements forming a surface of the shape represented by the first element group, if a distance between the first element and a second element corresponding to a position at which a straight line connecting the first element and the image capturing apparatus that has captured the first element intersects the surface does not exceed a predetermined threshold, the first element is excluded from a deletion target.