1,532 research outputs found

    Study on 3D modeling and pattern-making for upper garment(上衣の三次元モデルの構築およびパターンメーキングに関する研究)

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    信州大学(Shinshu university)博士(工学)ThesisZHANG JUN. Study on 3D modeling and pattern-making for upper garment(上衣の三次元モデルの構築およびパターンメーキングに関する研究). 信州大学, 2017, 博士論文. 博士(工学), 甲第663号, 平成29年03月20日授与.doctoral thesi

    Fit evaluation of virtual garment try-on by learning from digital pressure data

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    Presently, garment fit evaluation mainly focuses on real try-on, and rarely deals with virtual try-on. With the rapid development of E-commerce, there is a profound growth of garment purchases through the internet. In this context, fit evaluation of virtual garment try-on is vital in the clothing industry. In this paper, we propose a Naive Bayes-based model to evaluate garment fit. The inputs of the proposed model are digital clothing pressures of different body parts, generated from a 3D garment CAD software; while the output is the predicted result of garment fit (fit or unfit). To construct and train the proposed model, data on digital clothing pressures and garment real fit was collected for input and output learning data respectively. By learning from these data, our proposed model can predict garment fit rapidly and automatically without any real try-on; therefore, it can be applied to remote garment fit evaluation in the context of e-shopping. Finally, the effectiveness of our proposed method was validated using a set of test samples. Test results showed that digital clothing pressure is a better index than ease allowance to evaluate garment fit, and machine learning-based garment fit evaluation methods have higher prediction accuracies

    Real-time virtual fitting with body measurement and motion smoothing

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    Cataloged from PDF version of article.We present a novel virtual fitting room framework using a depth sensor, which provides a realistic fitting experience with customized motion filters, size adjustments and physical simulation. The proposed scaling method adjusts the avatar and determines a standardized apparel size according to the user's measurements, prepares the collision mesh and the physics simulation, with a total of 1 s preprocessing time. The real-time motion filters prevent unnatural artifacts due to the noise from depth sensor or self-occluded body parts. We apply bone splitting to realistically render the body parts near the joints. All components are integrated efficiently to keep the frame rate higher than previous works while not sacrificing realism. (C) 2014 Elsevier Ltd. All rights reserved

    Virtual Garment Creation

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    Applications of Virtual Reality

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    Information Technology is growing rapidly. With the birth of high-resolution graphics, high-speed computing and user interaction devices Virtual Reality has emerged as a major new technology in the mid 90es, last century. Virtual Reality technology is currently used in a broad range of applications. The best known are games, movies, simulations, therapy. From a manufacturing standpoint, there are some attractive applications including training, education, collaborative work and learning. This book provides an up-to-date discussion of the current research in Virtual Reality and its applications. It describes the current Virtual Reality state-of-the-art and points out many areas where there is still work to be done. We have chosen certain areas to cover in this book, which we believe will have potential significant impact on Virtual Reality and its applications. This book provides a definitive resource for wide variety of people including academicians, designers, developers, educators, engineers, practitioners, researchers, and graduate students

    Consumer adoption of the Internet for apparel shopping

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    The study explored the relationships among attitudinal, social, and behavioral variables associated with Internet apparel shopping. Study objectives were: (1) to examine consumers\u27 experience with the Internet, in-home apparel shopping, and Internet apparel shopping, (2) to propose theoretical models explaining consumer adoption of the Internet for apparel shopping by incorporating two social psychological theories---the theory of reasoned action and the theory of innovation adoption, and (3) to test the proposed models for respondents and subset groups (mail order shoppers and non-mail order shoppers);A self-administrated questionnaire was mailed to a random national sample of 1,600 households. A total of 448 questionnaires were returned, generating a 27.4% return rate. Of these, 355 usable questionnaires were submitted for data analysis using descriptive analysis, exploratory factor analysis, MANOVA, ANOVA, and structural equation modeling via LISREL VII and AMOS;Although respondents showed a tremendously increased adoption rate of Internet apparel shopping compared to previous research findings, respondents were still hesitant to shop for apparel through the Internet. Respondents indicated that they would shop for apparel more often through the Internet if there were some market incentives for Internet shoppers such as free and easier product returns, innovative functions (e.g., view of how the garment looks on their own body), and ensured credit card safety;Through causal model analyses, the decision making process of Internet adoption for apparel shopping was explained by three components: (1) belief-attitude-behavioral relationships, (2) social support and social acceptance, and (3) prior experience with the Internet. The hypothesized paths generated from the theory of reasoned action and the theory of innovation adoption were significant across the proposed models. Specifically, prior experience with the Internet had the strongest influence on apparel buying intention through the Internet across all models. No significant differences in parameter estimates were found between mail order and non-mail order shoppers. Age, education, and household income were important demographic variables affecting consumer adoption of Internet apparel shopping. Implications for industry and academia were generated based on findings

    Real-time Deep Dynamic Characters

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