Object Model Generation Using Topological Image Synthesis
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Solution Overview
Problem
Existing methods for generating object models are costly and require expensive image capturing devices and complex computer hardware, limiting their universality and efficiency.
Innovation Solution
A method that involves obtaining an initial morphable model, processing initial images and depth images to generate target topological images, and synthesizing models to create a target object model, which can be implemented in an electronic device or storage medium, reducing costs and improving generation accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If expensive image capturing devices and high-configured computer hardware are used, then the quality and accuracy of generated object models improve, but the cost and complexity of the system increase
Solution Approach 1:
The patent replaces expensive mechanical image capturing devices with software-based image processing algorithms. Specifically, it uses depth image processing, topological image generation, and morphable model synthesis to achieve accurate object model generation without requiring high-end cameras or specialized hardware. This substitutes a mechanical/optical system with a computational/software system.
Solution Approach 2:
The patent creates simplified representations (topological images and morphable models) that copy the essential geometric and structural information from original images. Instead of processing raw high-resolution images directly, it generates simplified topological copies that retain the necessary shape and structure information, reducing computational requirements while maintaining generation accuracy.
2Manufacturing precision
If expensive image capturing devices and complex hardware are used, then the quality of object model generation improves, but the cost increases
Solution Approach 1:
The patent replaces expensive hardware systems with software-based processing. It uses algorithms for depth image processing, topological transformation, and morphable model synthesis that can run on standard computers, eliminating the need for expensive specialized hardware and reducing overall system cost while maintaining generation quality.
Solution Approach 2:
The patent uses computationally inexpensive intermediate representations (topological images, morphable models) that can be generated and discarded during the processing pipeline. These temporary data structures enable complex model generation without requiring sustained high computational resources, reducing overall processing costs.
3Manufacturing precision
If expensive image capturing devices and complex hardware are used, then the accuracy of object model generation improves, but the universality and efficiency decrease
Solution Approach 1:
The patent segments the image processing task into distinct stages: depth image processing, topological image generation, and morphable model synthesis. Each stage processes simplified data representations, reducing computational complexity at each step and improving overall processing efficiency compared to processing raw images directly through a single complex pipeline.
Solution Approach 2:
The patent performs preliminary processing to convert raw images into topological images that capture essential geometric information. This preliminary transformation simplifies subsequent processing steps, enabling faster and more efficient model generation while maintaining accuracy, as the complex geometric relationships are already encoded in the topological representation.
Data Source
AI summary
A method for generating an object model includes: obtaining an initial morphable model; obtaining a plurality of initial images of an object, and depth images corresponding to the plurality of initial images; obtaining a plurality of target topological images by processing the plurality of initial images based on the depth images; obtaining a plurality of models to be synthesized by processing the initial morphable model based on the plurality of target topological images; and generating a target object model based on the plurality of models to be synthesized.