The Experts below are selected from a list of 10389 Experts worldwide ranked by ideXlab platform
Niloy J Mitra - One of the best experts on this subject based on the ideXlab platform.
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learning a shared shape space for multimodal Garment Design
ACM Transactions on Graphics, 2018Co-Authors: Tuanfeng Y Wang, Duygu Ceylan, Jovan Popovic, Niloy J MitraAbstract:Designing real and virtual Garments is becoming extremely demanding with rapidly changing fashion trends and increasing need for synthesizing realisticly dressed digital humans for various applications. This necessitates creating simple and effective workflows to facilitate authoring sewing patterns customized to Garment and target body shapes to achieve desired looks. Traditional workflow involves a trial-and-error procedure wherein a mannequin is draped to judge the resultant folds and the sewing pattern iteratively adjusted until the desired look is achieved. This requires time and experience. Instead, we present a data-driven approach wherein the user directly indicates desired fold patterns simply by sketching while our system estimates corresponding Garment and body shape parameters at interactive rates. The recovered parameters can then be further edited and the updated draped Garment previewed. Technically, we achieve this via a novel shared shape space that allows the user to seamlessly specify desired characteristics across multimodal input without requiring to run Garment simulation at Design time. We evaluate our approach qualitatively via a user study and quantitatively against test datasets, and demonstrate how our system can generate a rich quality of on-body Garments targeted for a range of body shapes while achieving desired fold characteristics. Code and data are available at our project webpage.
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learning a shared shape space for multimodal Garment Design
arXiv: Graphics, 2018Co-Authors: Tuanfeng Y Wang, Duygu Ceylan, Jovan Popovic, Niloy J MitraAbstract:Designing real and virtual Garments is becoming extremely demanding with rapidly changing fashion trends and increasing need for synthesizing realistic dressed digital humans for various applications. This necessitates creating simple and effective workflows to facilitate authoring sewing patterns customized to Garment and target body shapes to achieve desired looks. Traditional workflow involves a trial-and-error procedure wherein a mannequin is draped to judge the resultant folds and the sewing pattern iteratively adjusted until the desired look is achieved. This requires time and experience. Instead, we present a data-driven approach wherein the user directly indicates desired fold patterns simply by sketching while our system estimates corresponding Garment and body shape parameters at interactive rates. The recovered parameters can then be further edited and the updated draped Garment previewed. Technically, we achieve this via a novel shared shape space that allows the user to seamlessly specify desired characteristics across multimodal input {\em without} requiring to run Garment simulation at Design time. We evaluate our approach qualitatively via a user study and quantitatively against test datasets, and demonstrate how our system can generate a rich quality of on-body Garments targeted for a range of body shapes while achieving desired fold characteristics.
Xianyi Zeng - One of the best experts on this subject based on the ideXlab platform.
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Development of an Intelligent Data-Driven System to Recommend Personalized Fashion Design Solutions
'MDPI AG', 2021Co-Authors: Shukla Sharma, Xianyi Zeng, Ludovic Koehl, Pascal Bruniaux, Zhujun WangAbstract:In the context of fashion/textile innovations towards Industry 4.0, a variety of digital technologies, such as 3D Garment CAD, have been proposed to automate, optimize Design and manufacturing processes in the organizations of involved enterprises and supply chains as well as services such as marketing and sales. However, the current digital solutions rarely deal with key elements used in the fashion industry, including professional knowledge, as well as fashion and functional requirements of the customer and their relations with product technical parameters. Especially, product Design plays an essential role in the whole fashion supply chain and should be paid more attention to in the process of digitalization and intelligentization of fashion companies. In this context, we originally developed an interactive fashion and Garment Design system by systematically integrating a number of data-driven services of Garment Design recommendation, 3D virtual Garment fitting visualization, Design knowledge base, and Design parameters adjustment. This system enables close interactions between the Designer, consumer, and manufacturer around the virtual product corresponding to each Design solution. In this way, the complexity of the product Design process can drastically be reduced by directly integrating the consumer’s perception and professional Designer’s knowledge into the Garment computer-aided Design (CAD) environment. Furthermore, for a specific consumer profile, the related computations (Design solution recommendation and Design parameters adjustment) are performed by using a number of intelligent algorithms (BIRCH, adaptive Random Forest algorithms, and association mining) and matching with a formalized Design knowledge base. The proposed interactive Design system has been implemented and then exposed through the REST API, for Designing Garments meeting the consumer’s personalized fashion requirements by repeatedly running the cycle of Design recommendation—virtual Garment fitting—online evaluation of Designer and consumer—Design parameters adjustment—Design knowledge base creation, and updating. The effectiveness of the proposed system has been validated through a business case of personalized men’s shirt Design
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Knowledge-Based Open Performance Measurement System (KBO-PMS) for a Garment Product Development Process in Big Data Environment
IEEE Access, 2019Co-Authors: Yan Hong, Xianyi Zeng, Yuyang Wang, Wen Yang, Zhijuan PanAbstract:Globally, customers are getting increasingly demanding in terms of personalization of products and are asking for shorter product development periods with more predictable product performance, especially in fashion industry. Current market pressures drive firms to adapt new Design process in product development (PD) processes. Nevertheless, choosing the effective PD process is a challenging, complex decision. There is a critical need to develop a performance measurements system (PMS) for choosing appropriate product development (PD) processes in Garment Design to support product mangers to effectively respond to market. This paper presents a knowledge-based open performance measurement system (KBO-PMS) in big data environment, in order to support complex industrial decision-making for new product development. Its dynamic and flexible structure enables the whole system to be more adapted to knowledge sharing of product managers and processing of various time-varying data. The proposed KBO-PMS is composed of an interactive structure, capable of both integrating new KPIs from the open resource and tracking the evolution of the KBO-PMS components with time. The proposed KBO-PMS has been validated by realizing the performance evaluation of product development (PD) in fashion industry. It can be regarded as an application of open-resource based dynamic group decision-making in fashion big data environment.
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a customized Garment collaborative Design process by using virtual reality and sensory evaluation on Garment fit
Computers & Industrial Engineering, 2017Co-Authors: Xianyi Zeng, Xiao Chen, Ludovic KoehlAbstract:Abstract As the successful implantation of CAD (computer-aided-Design) technology in Garment industry, the 3D virtual Garment technology has attracted a great attention of textile/Garment companies. However, wearer’s perception on virtual Garment in terms of fitting and comfort has never been systematically studied. In this paper, we propose an original customized 3D Garment collaborative Design process by integrating interactions between the Designer and the specific consumer. In this context, a normalized sensory evaluation on Garment fitting effects will be organized in a virtual environment, in order to enhance communications of the concerned actors on perception of products. Also, by learning from the measured distances between the Garment surfaces and the mannequin (input) and sensory descriptors (output), we model the relationship between the Garment Design parameters and the human perception on fit of the finished virtual products. Using this model, we can estimate the fit perception for a specific Garment size on a specific body shape without any real try-on experience. In practice, the proposed collaborative Design process will permit to develop an online recommendation system for Garment size selection and fit estimation. Furthermore, it will permit to recursively modify the initial Garment patterns according to the consumer’s fit preferences so that they can obtain a real personalized Garment. In this way, the consumer will be directly involved in the product Design process by performing a series of sensory evaluations on virtual Garment fit in order to obtain a desired finished product. This process has been validated by creating a collection of T-shirts meeting requirements of various customers.
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virtual reality based collaborative Design method for Designing customized Garment for disabled people with scoliosis
International Journal of Clothing Science and Technology, 2017Co-Authors: Yan Hong, Kaixuan Liu, Xianyi Zeng, Pascal Bruniaux, Yan Chen, Min DongAbstract:Purpose The purpose of this paper is to present a new collaborative Design-based method for Designing customized Garments, aimed at the physically disabled people with scoliosis. Design/methodology/approach The proposed method is based on the virtual human model created using a 3D body scanner, permitting to simulate the consumer’s morphological shape with atypical physical deformations. Next, customized 2D and 3D virtual Garment prototyping tools will be used to create products through interactions between the consumer, Designer and pattern maker. The general principle of the proposed Design method is based on the following sequence: Design-display-evaluation-adjustment. After running the sequence for a number of times, the final Design solution, which will be approved by both the Designer and consumer, can be easily identified. Findings Design knowledge, which is already applied to normal body shapes successfully can be applied to 3D Garment Design using the concept which is based on collaborative Design. Through this process, the classical 2D Garment Design knowledge, especially 2D patterns and Design rules, can be modified and applied according to a normalized virtual Garment sensory evaluation procedure quantitatively. This evaluation procedure, interactively performed by the Designer and consumer, can permit to adapt the finished product to disabled people afflicted with severe scoliosis. The proposed method is also validated to be more advanced compared to 2D-to-3D virtual CAD Design method, especially for atypical morphologies. Originality/value As a co-Design method, 3D virtual draping and sensory evaluation can fully satisfy the interaction between the Garment Design technical space and perceptual space of the finished Garments ensuring desired 3D Garment fit effect by adjustment of technical parameters. 3D scanning technology is used to generate a complete digitalized 3D human model, permitting to extract the main features of body shapes without accurate measurements. As a knowledge-based Design process, both the fashion Design knowledge and the pattern making knowledge will be extracted to provide inspirations and references. Successful Design solutions will be incorporated into the fashion Design knowledge base in order to generate new Design rules and enhance professional Design knowledge.
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sensory evaluation based fuzzy ahp approach for material selection in customized Garment Design and development process
Microelectronics Systems Education, 2016Co-Authors: Xianyi Zeng, Yan Hong, Pascal Bruniaux, A Curteza, Yan ChenAbstract:Material selection is the most difficult section in the customized Garment product Design and development process. This study aims to create a hierarchical framework for material selection. The analytic hierarchy process and fuzzy sets theories have been applied to mindshare the diverse requirements from the customer and inherent interaction/interdependencies among these requirements. Sensory evaluation ensures a quick and effective selection without complex laboratory test such as KES and FAST, using the professional knowledge of the Designers. A real empirical application for the physically disabled people is carried out to demonstrate the proposed method. Both the theoretical and practical background of this paper have indicated the fuzzy analytical network process can capture expert's knowledge existing in the form of incomplete, ambiguous and vague information for the mutual influence on attribute and criteria of the material selection.
Wei Chen - One of the best experts on this subject based on the ideXlab platform.
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smart rehabilitation Garment for posture monitoring
International Conference of the IEEE Engineering in Medicine and Biology Society, 2015Co-Authors: Qi Wang, Wei Chen, Aaa Annick Timmermans, C Karachristos, Jbos Jeanbernard Martens, Panos MarkopoulosAbstract:Posture monitoring and correction technologies can support prevention and treatment of spinal pain or can help detect and avoid compensatory movements during the neurological rehabilitation of upper extremities, which can be very important to ensure their effectiveness. We describe the Design and development of Smart Rehabilitation Garment (SRG) a wearable system Designed to support posture correction. The SRG combines a number of inertial measurement units (IMUs), controlled by an Arduino processor. It provides feedback with vibration on the Garment, audible alarm signals and visual instruction through a Bluetooth connected smartphone. We discuss the placement of sensing modules, the Garment Design, the feedback Design and the integration of smart textiles and wearable electronics which aimed at achieving wearability and ease of use. We report on the system's accuracy as compared to optical tracker method.
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smart Garment Design for rehabilitation
NeuroRehabilitation, 2014Co-Authors: Qi Wang, Wei Chen, Panos MarkopoulosAbstract:During rehabilitation training posture monitoring is very important for enhancing training effectiveness. This article presents the Design and implementation of a smart rehabilitation Garment (SRG) to support posture correction. The Garment the Design and implementation of a smart rehabilitation Garment (SRG) to support posture correction. The Garment has been Designed to supports posture monitoring feedback, during training. The Garment consists of accelerometers in various positions with smart textile integration, controlled by a Lilypad Arduino processor which also controls vibrator motors that provide tactile feedback to patients. The SRG is driven by a software application running on a smartphone or personal computer by Bluetooth, which presents fine grain feedback, and training results and reminders to patients. In this paper we focus on the sensing modules’ placements and embedded Design based on the integration of smart textiles. This work places particular emphasis on having a practical, wearable, and aesthetic device, as these are crucial elements for making the device useful in context and accepted by its users.
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smart rehabilitation Garment Design for arm hand training
International Conference on Pervasive Computing, 2014Co-Authors: Qi Wang, Panos Markopoulos, Wei ChenAbstract:This paper describes the Design of a smart rehabilitation Garment (SRG) to support posture correction during rehabilitation training. The Garment is equipped with accelerometers in various positions and is controlled by an Arduino processor. It connects with Bluetooth to a smartphone or a personal computer in order to provide feedback to patients. The Garment can provide reminders to users by vibration. We discuss the placement of sensing modules, the Garment Design and the integration of smart textiles and wearable electronics. The Garment has been Designed to support posture feedback during rehabilitation training, e.g., in the context of arm-hand training, or to be used as a posture correction aid worn throughout the day. We argue that wearability and comfort are major requirements in order to achieve acceptance by users.
Yan Hong - One of the best experts on this subject based on the ideXlab platform.
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Knowledge-Based Open Performance Measurement System (KBO-PMS) for a Garment Product Development Process in Big Data Environment
IEEE Access, 2019Co-Authors: Yan Hong, Xianyi Zeng, Yuyang Wang, Wen Yang, Zhijuan PanAbstract:Globally, customers are getting increasingly demanding in terms of personalization of products and are asking for shorter product development periods with more predictable product performance, especially in fashion industry. Current market pressures drive firms to adapt new Design process in product development (PD) processes. Nevertheless, choosing the effective PD process is a challenging, complex decision. There is a critical need to develop a performance measurements system (PMS) for choosing appropriate product development (PD) processes in Garment Design to support product mangers to effectively respond to market. This paper presents a knowledge-based open performance measurement system (KBO-PMS) in big data environment, in order to support complex industrial decision-making for new product development. Its dynamic and flexible structure enables the whole system to be more adapted to knowledge sharing of product managers and processing of various time-varying data. The proposed KBO-PMS is composed of an interactive structure, capable of both integrating new KPIs from the open resource and tracking the evolution of the KBO-PMS components with time. The proposed KBO-PMS has been validated by realizing the performance evaluation of product development (PD) in fashion industry. It can be regarded as an application of open-resource based dynamic group decision-making in fashion big data environment.
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virtual reality based collaborative Design method for Designing customized Garment for disabled people with scoliosis
International Journal of Clothing Science and Technology, 2017Co-Authors: Yan Hong, Kaixuan Liu, Xianyi Zeng, Pascal Bruniaux, Yan Chen, Min DongAbstract:Purpose The purpose of this paper is to present a new collaborative Design-based method for Designing customized Garments, aimed at the physically disabled people with scoliosis. Design/methodology/approach The proposed method is based on the virtual human model created using a 3D body scanner, permitting to simulate the consumer’s morphological shape with atypical physical deformations. Next, customized 2D and 3D virtual Garment prototyping tools will be used to create products through interactions between the consumer, Designer and pattern maker. The general principle of the proposed Design method is based on the following sequence: Design-display-evaluation-adjustment. After running the sequence for a number of times, the final Design solution, which will be approved by both the Designer and consumer, can be easily identified. Findings Design knowledge, which is already applied to normal body shapes successfully can be applied to 3D Garment Design using the concept which is based on collaborative Design. Through this process, the classical 2D Garment Design knowledge, especially 2D patterns and Design rules, can be modified and applied according to a normalized virtual Garment sensory evaluation procedure quantitatively. This evaluation procedure, interactively performed by the Designer and consumer, can permit to adapt the finished product to disabled people afflicted with severe scoliosis. The proposed method is also validated to be more advanced compared to 2D-to-3D virtual CAD Design method, especially for atypical morphologies. Originality/value As a co-Design method, 3D virtual draping and sensory evaluation can fully satisfy the interaction between the Garment Design technical space and perceptual space of the finished Garments ensuring desired 3D Garment fit effect by adjustment of technical parameters. 3D scanning technology is used to generate a complete digitalized 3D human model, permitting to extract the main features of body shapes without accurate measurements. As a knowledge-based Design process, both the fashion Design knowledge and the pattern making knowledge will be extracted to provide inspirations and references. Successful Design solutions will be incorporated into the fashion Design knowledge base in order to generate new Design rules and enhance professional Design knowledge.
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sensory evaluation based fuzzy ahp approach for material selection in customized Garment Design and development process
Microelectronics Systems Education, 2016Co-Authors: Xianyi Zeng, Yan Hong, Pascal Bruniaux, A Curteza, Yan ChenAbstract:Material selection is the most difficult section in the customized Garment product Design and development process. This study aims to create a hierarchical framework for material selection. The analytic hierarchy process and fuzzy sets theories have been applied to mindshare the diverse requirements from the customer and inherent interaction/interdependencies among these requirements. Sensory evaluation ensures a quick and effective selection without complex laboratory test such as KES and FAST, using the professional knowledge of the Designers. A real empirical application for the physically disabled people is carried out to demonstrate the proposed method. Both the theoretical and practical background of this paper have indicated the fuzzy analytical network process can capture expert's knowledge existing in the form of incomplete, ambiguous and vague information for the mutual influence on attribute and criteria of the material selection.
Dava J Newman - One of the best experts on this subject based on the ideXlab platform.
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morphing compression Garments for space medicine and extravehicular activity using active materials
Aerospace medicine and human performance, 2016Co-Authors: Bradley T Holschuh, Dava J NewmanAbstract:Compression Garments tend to be difficult to don/doff, due to their intentional function of squeezing the wearer. This is especially true for compression Garments used for space medicine and for extravehicular activity (EVA). We present an innovative solution to this problem by integrating shape changing materials-NiTi shape memory alloy (SMA) coil actuators formed into modular, 3D-printed cartridges-into compression Garments to produce Garments capable of constricting on command.A parameterized, 2-spring analytic counterpressure model based on 12 Garment and material inputs was developed to inform Garment Design. A methodology was developed for producing novel SMA cartridge systems to enable active compression Garment construction. Five active compression sleeve prototypes were manufactured and tested: each sleeve was placed on a rigid cylindrical object and counterpressure was measured as a function of spatial location and time before, during, and after the application of a step voltage input.Controllable active counterpressures were measured up to 34.3 kPa, exceeding the requirement for EVA life support (29.6 kPa). Prototypes which incorporated fabrics with linear properties closely matched analytic model predictions (4.1%/-10.5% error in passive/active pressure predictions); prototypes using nonlinear fabrics did not match model predictions (errors >100%). Pressure non-uniformities were observed due to friction and the rigid SMA cartridge structure.To our knowledge this is the first demonstration of controllable compression technology incorporating active materials, a novel contribution to the field of compression Garment Design. This technology could lead to easy-to-don compression Garments with widespread space and terrestrial applications.
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Morphing Compression Garments for Space Medicine and Extravehicular Activity Using Active Materials.
Aerospace medicine and human performance, 2016Co-Authors: Bradley T Holschuh, Dava J NewmanAbstract:INTRODUCTION: Compression Garments tend to be difficult to don/doff, due to their intentional function of squeezing the wearer. This is especially true for compression Garments used for space medicine and for extravehicular activity (EVA). We present an innovative solution to this problem by integrating shape changing materials-NiTi shape memory alloy (SMA) coil actuators formed into modular, 3D-printed cartridges-into compression Garments to produce Garments capable of constricting on command. METHODS: A parameterized, 2-spring analytic counterpressure model based on 12 Garment and material inputs was developed to inform Garment Design. A methodology was developed for producing novel SMA cartridge systems to enable active compression Garment construction. Five active compression sleeve prototypes were manufactured and tested: each sleeve was placed on a rigid cylindrical object and counterpressure was measured as a function of spatial location and time before, during, and after the application of a step voltage input. RESULTS: Controllable active counterpressures were measured up to 34.3 kPa, exceeding the requirement for EVA life support (29.6 kPa). Prototypes which incorporated fabrics with linear properties closely matched analytic model predictions (4.1%/-10.5% error in passive/active pressure predictions); prototypes using nonlinear fabrics did not match model predictions (errors >100%). Pressure non-uniformities were observed due to friction and the rigid SMA cartridge structure. DISCUSSION: To our knowledge this is the first demonstration of controllable compression technology incorporating active materials, a novel contribution to the field of compression Garment Design. This technology could lead to easy-to-don compression Garments with widespread space and terrestrial applications.
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low spring index niti coil actuators for use in active compression Garments
IEEE-ASME Transactions on Mechatronics, 2015Co-Authors: Brad Holschuh, Edward W Obropta, Dava J NewmanAbstract:This paper describes the modeling, development, and testing of low spring index nickel titanium (NiTi) coil actuators Designed for use in wearable compression Garments, and presents a prototype tourniquet system using these actuators. NiTi coil actuators produce both large forces (>1 N) and large recoverable displacements (>100% length) that are well suited for compression Garment Design. Thermomechanical coil models are presented that describe temperature and force as a function of nondimensionalized coil geometry, extensional strain, and applied voltage. These models suggest that low spring index coils maximize activation force, and an analytical model is presented to predict Garment counter-pressure based on actuator architecture. Several low spring index ( C $=$ 3.08) coils were manufactured, annealed, and tested to assess their detwinning and activation characteristics. Results suggest both annealing and applied stress affect activation thresholds. Actuator force increases both with extensional strain and applied voltage up to 7.24 N. A first-generation compression tourniquet system using integrated actuators with direct voltage control of applied pressure is presented, demonstrating >70% increase in applied pressure during activation. This approach enables new, dynamic Garments with controllable activation and low effort donning and doffing, with applications ranging from healthcare solutions to advanced space suit Design.
