Ultrawide-Angle Camera Registration for 3D Laser Scans
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Solution Overview
Problem
Existing 3D scanners require multiple images at different exposures for HDR imaging, which is time-consuming, and manual registration of scans is labor-intensive and prone to errors, especially in environments with large flat or curved surfaces.
Innovation Solution
A 3D scanner system with an ultrawide-angle lens camera that captures color images and registers scans by partitioning images into concentric regions, adjusting for lens distortion, and aligning 3D point clouds based on matching features in ultrawide-angle images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If HDR techniques are used to provide enhanced color images with accurate color representation, then image quality is improved, but the time required for acquiring images increases significantly
Solution Approach 1:
The patent segments the image acquisition process by using multiple cameras with different exposure settings simultaneously captured in one shot, rather than sequentially capturing multiple images. This is achieved through a beam splitter that divides the light path to multiple cameras, allowing parallel capture of different exposure levels and eliminating the time penalty of sequential HDR capture.
Solution Approach 2:
The patent uses periodic action by implementing a rolling shutter mechanism that sequentially reads out different regions of the image sensor at different exposure levels within a single continuous exposure period. This allows the system to capture multiple exposure levels in a periodic manner during one exposure cycle, reducing total acquisition time while maintaining HDR quality.
2Reliability
If manual registration of scans is performed, then registration can be done with existing methods, but the process is labor-intensive and prone to errors
Solution Approach 1:
The patent implements self-service by enabling automatic registration of 3D scans through feature matching in the captured images. The system automatically identifies corresponding features across multiple scans and computes transformation parameters without human intervention, making the registration process self-executing and eliminating manual labor while maintaining or improving accuracy through consistent algorithmic application.
Solution Approach 2:
The patent replaces the mechanical/manual registration process with an automated computational system. Instead of manual alignment operations, the system uses image processing algorithms to detect features, match them across scans, and automatically compute registration transformations, substituting human manual operations with automated mechanical and computational processes.
3Manufacturing precision
If multiple images at different exposures are captured for HDR imaging, then color representation accuracy is improved, but the number of images required increases
Solution Approach 1:
The patent merges multiple exposure-level images into a single captured frame by using a beam splitter to direct light from the same scene simultaneously to multiple cameras or to different regions of a camera sensor. This combining approach captures what would normally require multiple separate images into one synchronized capture, reducing the quantity of images while maintaining the color representation accuracy of HDR.
Solution Approach 2:
The patent adds a spatial dimension to the exposure variation by using a beam splitter to create multiple optical paths that diverge in space. Each camera or sensor region receives light at different exposure levels simultaneously, transforming the temporal sequence of multiple image captures into a spatial arrangement captured in a single moment, thereby reducing the total number of images required.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Reduces the time required for acquiring color images and automates the registration process, improving efficiency and accuracy in generating enhanced color 3D scans.
Implementation Method 1
a camera that captures an image of the surrounding environment, the image captures color information of the surrounding environment
Implementation Method 2
A TOF laser scanner is a scanner in which the distance to a target point is determined based on the speed of light in air between the scanner and a target point
Data Source
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AI summary
According to one or more embodiments, a method includes capturing a first three-dimensional (3D) point cloud and a second 3D point cloud. Each of the 3D point clouds includes a plurality 3D coordinates corresponding to one or more objects scanned in a surrounding environment. The first 3D point cloud and the second 3D point cloud capturing at least one overlapping portion. Further, the method includes capturing a first ultrawide-angle image and a second ultrawide-angle image of the surrounding environment, the first ultrawide-angle image captures color information of the first 3D point cloud, and the second ultrawide-angle image captures color information of the second 3D point cloud. The method further includes registering the first 3D point cloud and the second 3D point cloud by mapping one or more features from the first ultrawide-angle image and the second ultrawide-angle image.