Point Cloud Attribute Assignment via 3D Visualization and Image Segmentation
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Solution Overview
Problem
Existing point cloud data processing techniques are inefficient and prone to errors when assigning attribute information to complex or overlapping objects, as manual selection of points is time-consuming and can lead to inaccurate assignments, especially when objects are complicated or overlap in two-dimensional image data.
Innovation Solution
A point cloud data processing apparatus and method that enables three-dimensional rotation, movement, and rescaling of point cloud data, allowing for accurate selection of regions on image data, with optional machine learning-based recognition for efficient and precise assignment of attribute information to corresponding points.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual point selection is used to assign attribute information, then flexibility and precision in selection are improved, but time consumption and operational efficiency deteriorate
Solution Approach 1:
The system performs automatic point cloud segmentation and attribute assignment based on image data and machine learning algorithms, eliminating the need for manual point selection. The computer automatically identifies objects, segments point clouds, and assigns attributes, making the system self-sufficient and highly efficient.
Solution Approach 2:
The patent replaces manual mechanical point selection with automated image processing and machine learning systems. Image data serves as a reference guide, and algorithms automatically identify and segment point cloud regions, substituting human manual operations with computational processes.
2Ease of operation
If two-dimensional image data is used for object selection, then ease of operation is improved, but selection accuracy deteriorates due to hidden objects
Solution Approach 1:
The patent transitions from two-dimensional image selection to three-dimensional point cloud visualization. By displaying selected point cloud regions in 3D space, the system allows users to verify selections from multiple angles, ensuring that all objects are correctly identified even when they overlap in 2D images.
Solution Approach 2:
The system provides visual feedback by displaying the selected point cloud region in three-dimensional space after automatic segmentation. This feedback mechanism allows users to verify the accuracy of automatic selection and make corrections if needed, improving overall selection precision.
3Measurement precision
If point cloud data is displayed in three-dimensional space with rotation and scaling, then selection accuracy is improved, but device complexity and computational requirements worsen
Solution Approach 1:
The patent segments the point cloud data into distinct regions corresponding to different objects before display. By pre-processing and dividing the point cloud into manageable segments based on image data references, the system reduces the complexity of handling large-scale 3D point cloud data while maintaining selection accuracy.
Solution Approach 2:
The system performs preliminary segmentation and identification of point cloud regions based on image data before the actual attribute assignment process. This preliminary action prepares the data in advance, reducing the computational burden during interactive selection and display operations.
Data Source
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AI summary
There are provided a point cloud data processing apparatus, a point cloud data processing method, and a program with which attribute information can be efficiently and accurately assigned to a point cloud. A point cloud data processing apparatus (11) includes: a memory (21) configured to store point cloud data (7) and pieces of image data (5), with positions of pixels of at least any one piece of image data (5) among the pieces of image data (5) being associated with points that constitute the point cloud data (7); and a processor, the processor being configured to cause a display unit (9) to display the point cloud data such that three-dimensional rotation, three-dimensional movement, and rescaling are enabled, accept a designation of a specified point in the point cloud data (7) displayed on the display unit (9), select a region of a target object including a region corresponding to the specified point, on the piece of image data (5), and assign the same attribute information to points, in the point cloud data (7), corresponding to the region of the target object.