Marker-Based CG Model Arrangement for Mixed Reality
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Solution Overview
Problem
Existing systems for superimposing and displaying CG models in real space require inefficient user selection and estimation of the relationship between object and CG model positions and attitudes.
Innovation Solution
An arranging apparatus and method that utilize processors to acquire three-dimensional positions of markers on an object, select a corresponding CG model, estimate the relative positions and attitudes between the CG model and the object, and arrange the CG model to overlap with the object in a specific space.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If a distance sensor is mounted to calculate the relationship between object and CG model based on distance image and depth value, then the position and attitude relationship can be determined, but the user still needs to manually select the CG model which reduces efficiency
Solution Approach 1:
The system automatically detects markers on objects, identifies the objects, selects appropriate CG models, and estimates position-attitude relationships without requiring user intervention. The system serves itself by autonomously completing the entire workflow from object detection to CG model arrangement.
Solution Approach 2:
Markers are introduced as intermediary elements attached to objects. These markers serve as mediators between the physical object and the digital CG model, enabling automatic recognition and association. The markers provide detectable features that bridge the gap between real-world objects and virtual model selection.
2Productivity
If manual selection of CG model is required, then the system can display desired models, but the preparation time and user burden increase significantly
Solution Approach 1:
Multiple CG models are pre-prepared and stored in the system before runtime. The system performs preliminary classification and organization of CG models, so that when an object is detected, the appropriate model can be immediately selected and arranged without requiring user search or selection during operation.
Solution Approach 2:
The system automatically performs the entire workflow including object detection via marker recognition, CG model selection based on object identification, and position-attitude estimation. This self-service approach eliminates manual user actions and significantly reduces preparation time.
3Adaptability or versatility
If markers are arranged on objects for detection, then automatic object recognition is enabled, but the device complexity increases due to additional components
Solution Approach 1:
Markers serve as intermediary detection targets that simplify object recognition. Instead of directly analyzing complex object features, the system detects the simpler, standardized marker patterns and uses them as proxies to identify and track objects, thereby enabling recognition without direct complex object analysis.
Solution Approach 2:
The system creates a simplified digital representation (copy) of the object through marker detection rather than analyzing the full complexity of the actual object. The marker provides a copied, simplified version of object identity and position that is easier to process computationally.
Data Source
AI summary
An arranging apparatus arranges a CG model with a shape approximately matching a shape of an object in a specific space so that the CG model overlaps with the object. The arranging apparatus acquires three-dimensional positions of a plurality of markers arranged on a first object. The arranging apparatus selects a first CG model of which a shape approximately matches a shape of the first object based on the three-dimensional positions of the plurality of markers. The arranging apparatus estimates a relationship of relative positions and attitudes between the selected first CG model and the first object based on the three-dimensional positions of the plurality of markers. The arranging apparatus arranges the first CG model in the specific space so as to overlap with the first object based on the estimated relationship of positions and attitudes.