Zooming Grid Segmentation for Vector Data Visualization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current zooming techniques in vector-based software rendering applications, especially on mobile devices, are inefficient as they either transform every object slowly or lose context by removing objects, due to the need for separate transformations for each marker and text element to maintain position and size, leading to choppy interactions, especially with large data sets.
Innovation Solution
The solution involves assigning graphic objects to grid elements, determining which objects are within the viewable area, and applying transformations only to those objects, thereby reducing processing requirements and maintaining context during zooming.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If transformations are applied to all graphic objects during zooming, then the completeness of the visualization is maintained, but the processing time increases significantly
Solution Approach 1:
The patent divides the graphic objects into multiple groups based on their spatial relationship to the viewport. Specifically, it segments objects into those that are fully visible, partially visible, or completely outside the viewport. This segmentation allows the system to apply transformations selectively only to objects that will be visible after zooming, rather than transforming all objects uniformly, thus reducing processing time while maintaining visual completeness.
2Manufacturing precision
If separate transformations are applied to each marker and text element to maintain position and size, then the accuracy of marker positioning is improved, but the processing complexity increases
Solution Approach 1:
The patent merges the transformation operations for markers and text elements by applying a unified transformation matrix to both types of objects. Instead of calculating separate transformations for each object type, the system uses a single transformation approach that handles both markers and text elements simultaneously, reducing computational complexity while maintaining positioning accuracy through the use of a consistent transformation framework.
3Loss of information
If all graphic objects are transformed during zooming, then the context of the entire image is maintained, but the processing speed decreases
Solution Approach 1:
The patent applies local quality by differentiating the transformation treatment based on the spatial location of graphic objects relative to the viewport. Objects within or near the viewport receive full transformation processing to maintain local visual quality and context, while objects far from the viewport are excluded from transformation. This localized approach preserves contextual information for visible areas while improving overall processing speed by skipping unnecessary transformations.
Data Source
AI summary
Example embodiments reduce the processing required to zoom on graphical data visualizations by transforming only graphic elements visible in the zooming viewport. In one example embodiment, a grid overlays the component image. Prior to zooming, grid elements covered by the zooming viewport are determined and only graphic objects bounded by those grid elements are transformed during zooming.