Abstract: A multi-material printer for using multiple materials, e.g., bioinks, to quickly fabricate structures, such as high-throughput screening microfluidic chips. The printer’s light projector for emits light in an exposure sequence to cure material in an additive manufacturing process. The printer further includes a motion stage operable to move a build platform into and out of the reservoir in coordination with the exposure sequence. The printer further includes an indexing stage having a work table for supporting the reservoir. The indexing stage is operable to selectively align the build platform with multiple different materials of the reservoir. The multiple materials may be arranged at distinct angular positions within a single reservoir, and the indexing stage may be operable to rotate the work table to align the build platform with different materials during the exposure sequence for a quick transition among different materials without refilling of materials, exchange of reservoirs, etc.

Abstract: 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.

Abstract: 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.

Abstract: The invention presents a system and a method for digitizing body shape from dressed human image using machine learning and optimization techniques. The invention is able to rapidly and accurately reconstruct human body shape without using costly, bulky and hazardous 3D scanners. Firstly, the system reconstructing human body shape from the dressed human image includes 2 main modules and 2 supplementary blocks, which are: (1) Input Block, (2) Pre-Processing Module, (3) Optimization Module, (4) Output Block. In which, the Pre-Processing Module comprises 4 blocks: (1) Image Standardization, (2) Clothes Classification and Segmentation, (3) Human Pose Estimation, (4) Cloth-Skin Displacement Model. The Optimization Modules comprises 2 blocks: (1) Human Parametric Model, (2) Human Parametric Optimization.