3D Human Body Model Reconstruction Using Single Viewpoint Depth Data
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Solution Overview
Problem
Conventional 3D modeling technologies that use depth data from a single viewpoint to create a full 3D human body model are computationally expensive and often produce inaccurate results due to the high computation cost and complexity of generating a full 3D model.
Innovation Solution
A VR-based apparatus that uses a reference 3D human body model with stored structural information and shape variations, deforms this model based on depth values captured from a single viewpoint to generate a reconstructed 3D model, reducing computational cost while maintaining accuracy by determining optimal shape and pose parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If depth data from a single viewpoint is used to generate a full 3D human body model, then the system cost is reduced, but the computational cost increases and manufacturing precision deteriorates
Solution Approach 1:
The method performs preliminary actions by capturing depth data from multiple viewpoints in advance and generating an initial 3D model before refinement. This preliminary 3D model serves as a foundation that reduces the computational burden of subsequent processing while maintaining accuracy through iterative optimization against the pre-captured depth data.
Solution Approach 2:
The system dynamically adjusts the modeling process by iteratively refining the 3D model based on comparison with captured depth data. The computational complexity is distributed across multiple iterations rather than requiring a single complex calculation, allowing the system to achieve high precision without overwhelming computational cost.
2Ease of manufacture
If depth data from a single viewpoint is used to generate a full 3D human body model, then the system cost is reduced, but the computational cost increases
Solution Approach 1:
The computational process is segmented into distinct stages: initial model generation from captured depth data, comparison with reference models, and iterative refinement. This segmentation allows each computational stage to be optimized independently, reducing the overall computational cost while maintaining the ability to generate accurate full 3D models from single viewpoint data.
3Manufacturing precision
If multiple stereo cameras are used to capture the human body from a plurality of viewpoints, then the manufacturing precision is improved, but the device complexity increases
Solution Approach 1:
The system uses a reference 3D human body model as a template or copy that is deformed and adjusted to match the captured depth data. This reference model approach allows the system to achieve high shape accuracy without requiring complex multi-camera setups, as the reference model provides a structured foundation that simplifies the reconstruction process from single viewpoint data.
Data Source
AI summary
Virtual reality-based apparatus that includes a memory device, a depth sensor and a modeling circuitry, captures a plurality of depth values of a first human subject from a single viewpoint using the depth sensor. The memory device stores a reference three dimensional (3D) human body model that comprises a mean body shape and a set of body shape variations. The modeling circuitry determines a first shape of the first human subject based on the plurality of depth values and generates a first deformed 3D human body model by deformation of the mean body shape. The modeling circuitry determines a first plurality of pose parameters for a first pose based on a plurality of rigid transformation matrices. The modeling circuitry generates a second deformed 3D human body model by deformation of a plurality of vertices and controls display of the second deformed 3D human body model as a reconstructed 3D model.