3D Human Reconstruction Using Compact Depth Camera Kit
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Solution Overview
Problem
Traditional 3D human reconstruction methods require extensive data collection, are prone to noise and errors, necessitate costly and potentially hazardous bulky systems, and can only capture static human shapes, limiting their applicability.
Innovation Solution
A compact system using four main blocks: Data Collection, Point Clouds Standardization, Human Digitization, and Output, employing two depth cameras to synchronize and process point cloud data, remove noise, and generate a parametric human model with movable skeleton joints, reducing data requirements and system complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If traditional 3D scanning methods are used to reconstruct human body, then complete human body can be reconstructed, but a large amount of data needs to be collected and processed
Solution Approach 1:
The patent divides the human body reconstruction into segmented processing using parametric models for different body parts (head, torso, limbs), allowing reconstruction from fewer point clouds by processing each segment independently with optimized parameters
Solution Approach 2:
The patent transforms the reconstruction approach by changing from direct point cloud processing to parametric model fitting, where a small set of parameters (pose, shape, appearance) controls the entire 3D model, dramatically reducing data requirements
2Manufacturing precision
If traditional 3D scanning methods are used to reconstruct human body, then reconstruction can be performed, but processing time is long and computation resources are high
Solution Approach 1:
The patent performs preliminary action by pre-defining parametric models with fixed topology and structure, so that during reconstruction only parameter optimization is needed rather than full mesh processing, significantly reducing computation time
Solution Approach 2:
The patent replaces the mechanical point cloud processing system with a mathematical optimization system that fits parametric models to point cloud data, reducing computational complexity from O(N) to O(1) where N is the number of points
3Measurement precision
If structured-light 3D scanning systems are used, then depth information can be acquired, but potential health risk and discomfort are caused to the person being digitized
Solution Approach 1:
The patent substitutes structured-light scanning with depth camera-based systems that use passive optical fields or safe infrared illumination, eliminating the harmful high-intensity light while maintaining depth measurement capability through alternative physical mechanisms
4Manufacturing precision
If traditional 3D scanning systems are used, then human body can be digitized, but the system is complex and bulky with great cost
Solution Approach 1:
The patent extracts only the essential function of depth measurement from complex scanning systems, using simplified depth cameras that capture depth information without the bulky structured-light projection equipment, reducing system complexity while maintaining digitization capability
Solution Approach 2:
The patent makes the depth camera system universal by using standard camera components that can serve multiple purposes (depth mapping, pose estimation, shape reconstruction) rather than requiring specialized equipment for each function
5Manufacturing precision
If traditional 3D scanning methods are used, then static human body shapes can be digitized, but the 3D human model is unable to move
Solution Approach 1:
The patent transforms the static 3D model into a dynamic one by introducing parametric control variables (pose parameters, shape parameters) that allow the model to deform and move while maintaining anatomical correctness through the parametric framework
Data Source
AI summary
The invention presents a system and a method for 3D human reconstruction using a compact kit of depth cameras. Instead of using complex and expensive devices as in traditional methods, the proposed system and method employs a simple, easy-to-install system to accurately collect the human body shape. The generated model is capable of moving thanks to a skeleton system simulating the human skeleton. The proposed system includes four blocks: Data Collection Block, Point Cloud Standardization Block, Human Digitization Block and Output Block. The proposed method includes five steps: Point Cloud Collecting, Point Cloud Filtering, Point Cloud Calibrating, Point Cloud Optimizing and 3D Human Model Generating.