3D Model Placement from 2D Room Images for Virtual Layout Accuracy
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Solution Overview
Problem
Existing room design tools face challenges in accurately adapting object layouts from 2D images to virtual environments due to size, shape, and parameter discrepancies, requiring manual user selection and placement, which is tedious and time-consuming.
Innovation Solution
A system that generates an algorithmically determined arrangement of 3D models in a virtual environment based on 2D images, utilizing stored physical attributes of objects and virtual environment parameters, automating the placement process without manual user selection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual selection of objects and locations is used, then placement accuracy can be controlled, but user effort and time consumption increase significantly
Solution Approach 1:
The system automatically determines object placements by analyzing the 2D image and computing 3D coordinates without requiring user intervention. The algorithm independently handles object detection, layout analysis, and placement determination, making the system self-sufficient for the placement task while maintaining accuracy through automated spatial reasoning.
Solution Approach 2:
The patent replaces the manual mechanical process of selecting and placing objects with an automated computational system. The algorithm processes the 2D image data, extracts spatial relationships, and automatically computes 3D placement coordinates, substituting human manual operations with automated image analysis and coordinate transformation mechanisms.
2Productivity
If automated placement algorithm is used, then productivity increases, but adaptability to different room parameters decreases
Solution Approach 1:
The placement algorithm dynamically adapts to different room parameters by processing the specific 2D image provided for each room. The system adjusts its analysis and placement computations based on the actual dimensions, layout, and characteristics of each room, making the algorithm flexible and adaptable rather than rigid and fixed.
Solution Approach 2:
The system handles variations in room parameters by transforming the 2D image data into 3D placement coordinates specific to each room's dimensions and layout. The algorithm modifies its output based on the input image's scale, orientation, and spatial relationships, allowing it to adapt to different room sizes and configurations while maintaining automated efficiency.
3Ease of operation
If 2D image layout is directly transferred to 3D environment, then ease of operation improves, but manufacturing precision deteriorates due to parameter differences
Solution Approach 1:
The patent replaces direct manual transfer of 2D layouts with automated image analysis and coordinate transformation. The system uses algorithms to detect objects in the 2D image, analyze their spatial relationships, and compute accurate 3D placement coordinates, substituting imprecise manual operations with precise computational processes.
Solution Approach 2:
The system transitions from 2D image space to 3D virtual environment by performing coordinate transformation. The algorithm extracts two-dimensional spatial relationships from the image and converts them into three-dimensional placement coordinates, adding the depth dimension while maintaining accuracy through mathematical transformation rather than direct transfer.
Data Source
AI summary
Systems and methods for composing a virtual environment are provided. The virtual environment may represent a room or other space having specified parameters. The system may facilitate placement of 3D models of objects in the virtual environment, where the 3D models correspond to one or more objects depicted in a 2D image, and the placement of the 3D models is algorithmically determined based on placement rules to generate an arrangement of the 3D models based on a layout of the one or more objects in the 2D image. The system can execute the placement rules to algorithmically determine placement locations of the 3D models corresponding to objects depicted in the 2D image.