3D Line Segment Generation From Point Clouds
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Solution Overview
Problem
Existing methods for generating 3D line segments from 2D images often result in false positives due to the assumption that 2D line segments across images represent the same real-world line segment, which may not always be accurate.
Innovation Solution
The method involves generating a 3D point cloud from multiple 2D images and then connecting 3D points that correspond to points along a 2D line segment in a 2D image to create a 3D line segment, thereby avoiding the pitfalls of triangulating 2D line segments across images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If 2D line segments from multiple images are triangulated to generate 3D line segments, then the process is simple and fast, but false positives occur when 2D segments represent different portions of the same real-world line segment
Solution Approach 1:
The patent segments the 3D line segment generation process into two distinct phases: (1) generating candidate 3D line segments through triangulation of 2D line segments, and (2) filtering candidates by validating whether their 2D projections align with actual 2D line segments in the input images. This segmentation allows the method to maintain computational efficiency while eliminating false positives through systematic validation.
Solution Approach 2:
The patent introduces 2D line segment detection as an intermediary validation step between triangulation and final 3D line segment output. By projecting candidate 3D line segments back to 2D space and checking alignment with detected 2D line segments, the method uses this intermediary check to filter false positives without requiring complex direct 3D validation.
2Ease of manufacture
If the assumption that 2D line segments represent the same real-world line segment is enforced, then triangulation can proceed straightforwardly, but accuracy decreases when occlusions cause 2D segments to represent different portions
Solution Approach 1:
The patent inverts the traditional triangulation approach by first generating candidate 3D line segments and then validating them against 2D line segment detections, rather than assuming correspondence and directly triangulating. This inversion allows the method to maintain computational simplicity while improving precision through post-generation validation that checks whether candidate segments actually correspond to visible 2D segments in the input images.
3Measurement precision
If additional validation steps are added to verify 2D line segment correspondence, then accuracy improves, but computational complexity and processing time increase
Solution Approach 1:
The patent extracts and leverages existing 2D line segment detection results as validation criteria for 3D line segment generation. By using the already-detected 2D line segments (and their associated geometric constraints) as a filter for candidate 3D segments, the method achieves high precision without adding substantial computational complexity, as the validation reuses existing detection outputs rather than requiring new complex processing.
Data Source
AI summary
Methods, storage media, and systems for generating a three-dimensional line segment are disclosed. Exemplary implementations may: receive a plurality of images: generate a point cloud based on the plurality of images; detect a two-dimensional line segment in a first image: project a set of 3d points of the plurality of 3d points as 2d points in the first image; select projected 3d points that are proximate to 2d points along the 2d line segment: and generate a 3d line segment by connecting 3d points of the point cloud represented by the selected projected 3d points.