3D Object Grouping via Spatial Proximity in Virtual Spaces
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Solution Overview
Problem
Users face difficulties in efficiently manipulating groups of related objects in three-dimensional graphic spaces, as existing technologies lack intuitive methods for automatic grouping and collective manipulation.
Innovation Solution
A control interface that allows users to select an initial object, initiate a grouping process by double-clicking, and recursively include nearby objects that meet a closeness criterion, enabling collective manipulation such as rotation, size adjustment, and positional adjustment around the centroid of the group, with visual indicators like bounding boxes for selected objects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual selection and grouping of multiple objects is performed individually, then grouping accuracy can be achieved, but user operation time and complexity increase significantly
Solution Approach 1:
The system automatically performs object grouping based on spatial proximity criteria without requiring manual selection of each object. When a user activates grouping mode, the system autonomously identifies objects meeting the closeness criterion and creates groups, eliminating the need for users to manually select and group each object individually.
Solution Approach 2:
The system uses a configurable closeness criterion parameter to automatically determine which objects should be grouped together. By adjusting this parameter, users can control the automatic grouping behavior to match different spatial relationships, allowing the system to adaptively group objects based on distance thresholds rather than manual selection.
2Productivity
If automatic grouping based on closeness criterion is implemented, then grouping efficiency improves, but control precision over individual object selection decreases
Solution Approach 1:
The system provides visual feedback by displaying bounding boxes around automatically grouped objects and highlighting selected objects. This feedback mechanism allows users to verify the automatic grouping results and make adjustments if needed, ensuring that the automated process produces accurate and intended groupings while maintaining high efficiency.
Solution Approach 2:
The grouping criterion is made dynamic and adjustable rather than fixed. Users can modify the closeness criterion parameter to adapt to different scenarios, allowing the automatic grouping to maintain precision across various object distributions and spatial configurations while preserving efficiency benefits.
3Adaptability or versatility
If group manipulation is enabled for multiple objects, then collective operation capability improves, but system complexity for managing individual object states increases
Solution Approach 1:
The system merges the state management of multiple selected objects into a single group entity. When objects are grouped, they are managed collectively through the group's bounding box and transformation operations, rather than tracking each object's state separately. This reduces system complexity by consolidating the management of multiple objects into unified group operations.
Solution Approach 2:
The group bounding box serves as an intermediary entity between the user and the individual objects within the group. Users interact with the group through the bounding box for selection, manipulation, and transformation, while the system automatically manages the individual object states. This intermediary simplifies the interface and reduces the complexity of directly managing multiple object states.
Data Source
AI summary
Aspects of the technology described herein provide a control interface for manipulating a 3-D graphical object within a virtual drawing space. The control can automatically group objects together for common manipulation. Example manipulations include position and orientation adjustments.