Point Cloud Annotation Clustering by Similarity
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The annotation process for point cloud data from measurement targets becomes complicated due to the large amount of data, requiring users to assign labels to numerous clusters, which decreases workability and increases operational complexity.
Innovation Solution
An annotation apparatus and method that generates clusters from point cloud data, determines a presentation order based on similarity, and presents them sequentially for label assignment, improving the efficiency of the annotation process by reducing the number of clusters displayed and automating range specification operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If all clusters are displayed on the display unit for user annotation, then the user can check all clusters, but the annotation work becomes complicated due to the enormous amount of point cloud data
Solution Approach 1:
The patent segments the enormous set of clusters into multiple pages, with each page displaying a manageable subset of clusters. The user can navigate through pages to annotate all clusters, but each page presents only a reasonable number of clusters at a time, making the annotation task more manageable and less complicated.
Solution Approach 2:
The system automatically generates clusters and calculates their similarity metrics before presentation to the user. This preliminary processing organizes the data structure and prepares the clusters for efficient annotation, reducing the cognitive load on the user during the actual annotation process.
2Productivity
If clusters are presented in arbitrary order, then all clusters can be displayed, but the annotation process becomes less efficient
Solution Approach 1:
The system performs preliminary sorting of clusters based on similarity metrics before presenting them to the user. By pre-organizing clusters in order of similarity, the system enables more efficient annotation where similar clusters can be annotated together, reducing the overall annotation time and improving productivity.
Solution Approach 2:
The patent changes the presentation parameter from arbitrary order to similarity-based order. This parameter change in how clusters are sequenced allows the user to annotate similar clusters in succession, improving efficiency by reducing context switching and making the annotation process more systematic.
Data Source
AI summary
An object of the present disclosure is to provide an annotation apparatus that can improve workability of annotation. An annotation apparatus (1) according to an example aspect of the present disclosure includes a cluster generation unit (11) configured to generate a plurality of clusters by grouping point cloud data corresponding to three-dimensional position information about a measurement target, a presentation order determination unit (12) configured to determine a presentation order of the plurality of clusters based on similarity between the generated plurality of clusters, a cluster presentation unit (13) configured to present the plurality of clusters in order based on the determined presentation order, and a label assignment unit (14) configured to assign a predetermined label to each of the clusters presented in the order.