Vector Design Object Hierarchy Clustering for Efficient Group Selection
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Solution Overview
Problem
Existing illustration computing systems face challenges in efficiently selecting and editing groups of graphical objects in vector designs, particularly due to limited selection tools and distortion caused by clustering methods that do not consider z-axis positions, leading to a burdensome user experience.
Innovation Solution
Generating an object hierarchy using a clustering algorithm that considers z-coordinate information and similarity scores based on attributes like color, stroke, size, and spatial placement, allowing for logical organization and efficient selection of object groups.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual selection of individual objects is used to create groups, then selection precision is improved, but user operation time and complexity increase significantly
Solution Approach 1:
The system performs automatic object grouping based on spatial proximity and visual attributes without requiring manual user intervention. The clustering algorithm autonomously identifies and groups related objects, eliminating the need for users to manually select each object while maintaining accurate grouping results.
Solution Approach 2:
The system transforms the selection process from manual coordinate-based selection to automated algorithm-based grouping using similarity thresholds. By changing the selection parameters from precise manual coordinates to automated similarity metrics, the system achieves both precision and efficiency.
2Productivity
If existing clustering methods are used to group similar objects, then grouping efficiency is improved, but visual appearance distortion occurs due to ignoring z-axis positions
Solution Approach 1:
The system extends traditional 2D clustering to 3D spatial clustering by incorporating z-axis depth information. This dimensional extension allows the clustering algorithm to respect the layered structure of vector designs, preventing visual distortion by maintaining proper occlusion relationships while still achieving efficient automatic grouping.
3Device complexity
If limited selection tools are used in editing tools, then device complexity is reduced, but ease of operation deteriorates due to burdensome user experience
Solution Approach 1:
The system automatically performs object grouping and selection expansion without requiring complex user interactions. When a user selects an object, the system autonomously identifies and includes related objects in the selection based on pre-computed clustering results, eliminating the need for complex multi-step selection procedures while maintaining simple tool interfaces.
Data Source
AI summary
This disclosure involves applying an edit to objects in a vector design corresponding to a selected level of an object hierarchy. A system accesses a vector design comprising first, second, and third objects, each of the objects having a respective axis coordinate. The system assigns the first object and the second object to or within a common level in an object hierarchy based on determining that a similarity score comparing the two objects exceeds a threshold and that a modification causing the axis coordinates of the two objects to be adjacent maintains an overlap between the third object and the two objects. The system receives a user input selecting the first object and expands the selection to the second object based on the second object being assigned to the common level. The system applies an edit to the first and second objects based on the expansion of the selection.