55 research outputs found

    Image-Based Virtual Clothing

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    Online shopping has found speedy growth for the fast-paced world in the present situation. Precisely garments shopping are one of the most exciting parts especially for ladies. The continuous changing fashion and newly designed outfits motivates customers for shopping. New online shopping stores have added an ease for shopping your desired products by removing the constraints of places and time limits. As far as garments are concerned, predicting the appropriate size and imaging the real life look of that garment just by viewing its image is a challenging task. The project introduces an easy and feasible solution for the online shopping try-on scenario by introducing an app with a digital try-on feature. It can enhance online shopping experience. In this project, we propose an idea for fitting a given 3D garment model on a person. We will use  3d models of the clothes that will fit on the image of the user and enable a user to see himself/herself wearing virtual clothes. The 3D models of the clothes are stored in the system. On opening the application, user can view the clothes available and by using the mobileā€™s camera the user can get an idea of how the garment will fit on him/her. This way the user can have a fair idea about the look of the garment

    Computational Design of Wiring Layout on Tight Suits with Minimal Motion Resistance

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    An increasing number of electronics are directly embedded on the clothing to monitor human status (e.g., skeletal motion) or provide haptic feedback. A specific challenge to prototype and fabricate such a clothing is to design the wiring layout, while minimizing the intervention to human motion. We address this challenge by formulating the topological optimization problem on the clothing surface as a deformation-weighted Steiner tree problem on a 3D clothing mesh. Our method proposed an energy function for minimizing strain energy in the wiring area under different motions, regularized by its total length. We built the physical prototype to verify the effectiveness of our method and conducted user study with participants of both design experts and smart cloth users. On three types of commercial products of smart clothing, the optimized layout design reduced wire strain energy by an average of 77% among 248 actions compared to baseline design, and 18% over the expert design.Comment: This work is accepted at SIGGRAPH ASIA 2023(Conference Track

    Applied 3D Virtual Try-on for Bodies with Atypical Characteristics

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    AbstractThe manufacture of clothing using real body measurements is based on user's new profile, on their own desire for individualization through purchased garments but also on the results of the anthropometric surveys which have shown great variability in morphological types, especially for women.Research conducted by the authors focused on the application of 3D virtual try-on in pattern alterations for ā€œwomen trousersā€. To achieve the objectives of the work, bodies with atypical characteristics were selected from the database resulting from 3D scanning of the Romanian women population. In the study, it was found that many women have different sizes for the two hip contours (left-right), differences being in the range 1.5 to 4.5cm.Based on these considerations a method of completion of the patterns for trousers has been developed and applied, by 3D simulation of the body-garment.This paper brings contributions to clothing design technology by 3D virtual try-on, taking into account the body shape of the users

    Customization and topology optimization of compression casts/braces on two-manifold surfaces

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    This paper applies the topology optimization (TO) technique to the design of custom compression casts/braces on two-manifold mesh surfaces. Conventional braces or casts, usually made of plaster or fiberglass, have the drawbacks of being heavy and unventilated to wear. To reduce the weight and improve the performance of a custom brace, TO methods are adopted to optimize the geometry of the brace in the three-dimensional (3D) space, but they are computationally expensive. Based on our observation that the brace has a much smaller thickness compared to other dimensions and the applied loads are normal forces, this paper presents a novel TO method based on thin plate elements on the two-dimensional manifold (2-manifold) surfaces instead of 3D solid elements. Our working pipeline starts from a 3D scan of a human body represented by a 2-manifold mesh surface, which is the base design domain for the custom brace. Similar to the concept of isoparametric representation, the 3D design domain is mapped onto a two-dimensional (2D) parametric domain. An Finite Element Analysis (FEA) with bending moments is performed on the parameterized 2D design domain, and the Solid Isotropic Material with Penalization (SIMP) method is applied to optimize the pattern in the parametric domain. After the optimized cast/brace is obtained on the 2-manifold mesh surface, a solid model is generated by our design interface and then sent to a 3D printer for fabrication. Compared with the optimization method with solid elements, our method is more efficient and controllable due to the high efficiency of solving FEA in the 2D domain

    Assessment and preliminary model development of shape memory polymers mechanical counter pressure space suits

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    Thesis (S.B.)--Massachusetts Institute of Technology, Dept. of Materials Science and Engineering, 2013.Cataloged from PDF version of thesis.Includes bibliographical references (p. 39-41).This thesis seeks to assess the viability of a space qualified shape memory polymer (SMP) mechanical counter pressure (MCP) suit. A key development objective identified by the International Space Exploration Coordination Group, the development of a superior space suit with greater mobility and environmental robustness is necessary to support long-range human space exploration, specifically a mission to Mars. Conceptualized in 1971, a spacesuit utilizing MCP would fulfill these goals but its development was halted due to inadequate mechanical analysis and material limitations at the time. Since then, new active materials have been assessed to potentially further the development of a space qualified MCP space suit, which include quantitative thresholds for minimum pressure production, durability, pressure distribution, mobility range, and ease of garment donning and doffing. Guided by these criteria, a SMP biaxial tubular braid applying MCP through active compression was designed and the prototype manufacturing processes were outlined. To predict the pressure production of this garment, the thermo-mechanics of a SMP was combined with the textile mechanics of a biaxial tubular braid and simulated within design parameter ranges consistent with the design criteria and practical considerations. The pressure production was controllable with the design parameters SMP elastic modulus, garment radial deformation, textile fiber spacing, and operational temperature. Assuming reasonable model accuracy, a SMP garment could achieve the necessary pressure production for a space qualified MCP suit, however, the durability of such a garment would be questionable considering the creep sustained from consecutive spacewalks of four to eight hours. Recommendations are made for methods to increase model accuracy, suggested SMP actuation mechanisms, and alternative textile architectures.by Brian Wee.S.B

    CAD-Based Porous Scaffold Design of Intervertebral Discs in Tissue Engineering

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    With the development and maturity of three-dimensional (3D) printing technology over the past decade, 3D printing has been widely investigated and applied in the field of tissue engineering to repair damaged tissues or organs, such as muscles, skin, and bones, Although a number of automated fabrication methods have been developed to create superior bio-scaffolds with specific surface properties and porosity, the major challenges still focus on how to fabricate 3D natural biodegradable scaffolds that have tailor properties such as intricate architecture, porosity, and interconnectivity in order to provide the needed structural integrity, strength, transport, and ideal microenvironment for cell- and tissue-growth. In this dissertation, a robust pipeline of fabricating bio-functional porous scaffolds of intervertebral discs based on different innovative porous design methodologies is illustrated. Firstly, a triply periodic minimal surface (TPMS) based parameterization method, which has overcome the integrity problem of traditional TPMS method, is presented in Chapter 3. Then, an implicit surface modeling (ISM) approach using tetrahedral implicit surface (TIS) is demonstrated and compared with the TPMS method in Chapter 4. In Chapter 5, we present an advanced porous design method with higher flexibility using anisotropic radial basis function (ARBF) and volumetric meshes. Based on all these advanced porous design methods, the 3D model of a bio-functional porous intervertebral disc scaffold can be easily designed and its physical model can also be manufactured through 3D printing. However, due to the unique shape of each intervertebral disc and the intricate topological relationship between the intervertebral discs and the spine, the accurate localization and segmentation of dysfunctional discs are regarded as another obstacle to fabricating porous 3D disc models. To that end, we discuss in Chapter 6 a segmentation technique of intervertebral discs from CT-scanned medical images by using deep convolutional neural networks. Additionally, some examples of applying different porous designs on the segmented intervertebral disc models are demonstrated in Chapter 6

    NON-RIGID BODY MECHANICAL PROPERTY RECOVERY FROM IMAGES AND VIDEOS

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    Material property has great importance in surgical simulation and virtual reality. The mechanical properties of the human soft tissue are critical to characterize the tissue deformation of each patient. Studies have shown that the tissue stiffness described by the tissue properties may indicate abnormal pathological process. The (recovered) elasticity parameters can assist surgeons to perform better pre-op surgical planning and enable medical robots to carry out personalized surgical procedures. Traditional elasticity parameters estimation methods rely largely on known external forces measured by special devices and strain field estimated by landmarks on the deformable bodies. Or they are limited to mechanical property estimation for quasi-static deformation. For virtual reality applications such as virtual try-on, garment material capturing is of equal significance as the geometry reconstruction. In this thesis, I present novel approaches for automatically estimating the material properties of soft bodies from images or from a video capturing the motion of the deformable body. I use a coupled simulation-optimization-identification framework to deform one soft body at its original, non-deformed state to match the deformed geometry of the same object in its deformed state. The optimal set of material parameters is thereby determined by minimizing the error metric function. This method can simultaneously recover the elasticity parameters of multiple regions of soft bodies using Finite Element Method-based simulation (of either linear or nonlinear materials undergoing large deformation) and particle-swarm optimization methods. I demonstrate the effectiveness of this approach on real-time interaction with virtual organs in patient-specific surgical simulation, using parameters acquired from low-resolution medical images. With the recovered elasticity parameters and the age of the prostate cancer patients as features, I build a cancer grading and staging classifier. The classifier achieves up to 91% for predicting cancer T-Stage and 88% for predicting Gleason score. To recover the mechanical properties of soft bodies from a video, I propose a method which couples statistical graphical model with FEM simulation. Using this method, I can recover the material properties of a soft ball from a high-speed camera video that captures the motion of the ball. Furthermore, I extend the material recovery framework to fabric material identification. I propose a novel method for garment material extraction from a single-view image and a learning based cloth material recovery method from a video recording the motion of the cloth. Most recent garment capturing techniques rely on acquiring multiple views of clothing, which may not always be readily available, especially in the case of pre-existing photographs from the web. As an alternative, I propose a method that can compute a 3D model of a human body and its outfit from a single photograph with little human interaction. My proposed learning-based cloth material type recovery method exploits simulated data-set and deep neural network. I demonstrate the effectiveness of my algorithms by re-purposing the reconstructed garments for virtual try-on, garment transfer, and cloth animation on digital characters. With the recovered mechanical properties, one can construct a virtual world with soft objects exhibiting real-world behaviors.Doctor of Philosoph
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