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67 lines (41 loc) · 5.34 KB
graph LR
    SMPL_Core_Model["SMPL Core Model"]
    SMPL_Parameter_Wrapper["SMPL Parameter Wrapper"]
    SMPL_Deformation_Utilities["SMPL Deformation Utilities"]
    SMPL_Initialization_Configuration["SMPL Initialization & Configuration"]
    SMPL_Parameter_Wrapper -- "prepares and formats input parameters for" --> SMPL_Core_Model
    SMPL_Core_Model -- "consumes the processed parameters provided by" --> SMPL_Parameter_Wrapper
    SMPL_Core_Model -- "invokes" --> SMPL_Deformation_Utilities
    SMPL_Initialization_Configuration -- "instantiates and configures" --> SMPL_Core_Model
    SMPL_Core_Model -- "relies on" --> SMPL_Initialization_Configuration
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Details

The 3D Body Model (SMPL) subsystem is a critical part of the ROMP project, focusing on the representation and manipulation of 3D human body models. It adheres to the "Core Models" and "Data Processing Pipeline" architectural patterns, providing the foundational elements for 3D human pose and shape estimation.

SMPL Core Model

This is the foundational component, embodying the SMPL mathematical model. It's responsible for generating 3D human meshes by applying pose and shape parameters and performing Linear Blend Skinning (LBS). It serves as the central representation of the 3D body.

Related Classes/Methods:

SMPL Parameter Wrapper

This component acts as an interface for the SMPL Core Model. Its primary role is to process and format input parameters (e.g., pose, shape, and potentially age-related adjustments) into the precise structure required by the SMPL Core Model. It also includes granular functions for parameter pre-processing.

Related Classes/Methods:

SMPL Deformation Utilities

These are low-level, reusable functions that perform the core mathematical and geometric operations necessary for deforming the SMPL mesh. This includes transformations, rotations, and blending of vertex positions based on joint movements and body shape.

Related Classes/Methods:

SMPL Initialization & Configuration

This component is responsible for the initial setup of the SMPL model, including loading necessary assets (e.g., joint regressors, blend shapes) and configuring the model for operation. It ensures the SMPL Core Model is correctly instantiated and prepared for use within the broader system.

Related Classes/Methods: