Point Cloud Assisted Photogrammetric Rendering
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Solution Overview
Problem
Current photogrammetric methods face challenges in accurately determining depth (Z coordinate) and visualizing details, particularly due to the dependency on the B/H ratio and operator interpretation, which limits the completeness and accuracy of three-dimensional representations.
Innovation Solution
A point cloud assisted photogrammetric restitution method that simultaneously visualizes stereoscopic images and point clouds acquired on the same coordinate system, allowing real-time alignment and accurate determination of depth through automated algorithms, thereby enhancing visualization and reducing misalignment errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional photogrammetric methods are used to determine depth, then the process requires manual operator interpretation and is time-consuming, but the accuracy and completeness of three-dimensional representation are limited
Solution Approach 1:
The patent replaces manual operator interpretation with automated algorithms that process point cloud data to determine depth. The system automatically matches stereoscopic image features with point cloud data, eliminating the need for manual measurement while improving both speed and accuracy of depth determination.
Solution Approach 2:
The system uses the point cloud data itself to provide depth information automatically. The point cloud, already containing three-dimensional coordinates, serves the dual purpose of both geometric representation and depth measurement, eliminating the need for separate manual depth determination processes.
2Productivity
If photogrammetric restitution is performed manually, then operator control and validation are maintained, but the speed and automation of depth calculation are limited
Solution Approach 1:
The patent implements automated algorithms that process point cloud data and stereoscopic images to calculate depth automatically. The system uses computational methods to match features and determine three-dimensional coordinates without manual intervention, significantly increasing processing speed while maintaining accuracy through automated validation mechanisms.
3Reliability
If point cloud data is used to determine depth, then independence from B/H ratio is achieved, but the complexity of data processing and alignment increases
Solution Approach 1:
The patent uses stereoscopic images as an intermediary to bridge the point cloud data and the final depth determination. The images serve as a reference framework that helps align and validate the point cloud data, making the complex processing more manageable through a structured approach of image-point cloud matching.
Solution Approach 2:
The system incorporates validation mechanisms that continuously check the consistency between point cloud data and stereoscopic image features. This feedback loop ensures that the depth determination is reliable by comparing automated results against visual verification, allowing for correction of alignment errors.
4Manufacturing precision
If manual stereoscopic observation is used, then operator judgment and control are maintained, but the precision and speed of three-dimensional vectoring are limited
Solution Approach 1:
The patent replaces manual three-dimensional vectoring with automated algorithms that process point cloud data to generate precise three-dimensional representations. The system automatically extracts lines and points from the point cloud, creating accurate three-dimensional models without manual intervention, thereby improving both precision and speed.
Data Source
AI summary
A point cloud assisted photogrammetric restitution method is described. Said method comprises:the simultaneous visualization on a screen (5) of the ensemble of a stereoscopic image (33) and a point cloud (34) acquired on a given area (2), said stereoscopic image deriving from at least a couple of photogrammetric images (11) acquired on said given area (2) and oriented according to the same coordinate system of the point cloud,the real time connection of the collimation mark (S) of the stereoscopic image with the corresponding collimation mark (S′) of the point cloud.