A Mixed Reality Virtual Clothes Try-On System

Yuan, Mingjun; Khan, Ishtiaq Rasool; Farbiz, Farzam; Yao, Susu; Niswar, Arthur; Foo, Min-Hui

doi:10.1109/tmm.2013.2280560

Cited by 84 publications

(41 citation statements)

References 27 publications

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“…In [11], a virtual try-on system using one Kinect was designed and three scenarios were displayed in the result as shown in Figure The system proposed by Zhang et al [12] was also Kinect-based. The workflows of the system is displayed in Figure 2.5.…”

Section: Virtual Try-on In 3dmentioning

confidence: 99%

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Customized 3D Clothes Modeling for Virtual Try-on System based on Multiple Kinects

Huang

Lee

2016

Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications

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Most existing 3D virtual try-on systems put clothes designed in one environment on a human captured in another environment, which cause the mismatching color and brightness problem. And also typical 3D clothes modeling starts with manually designed 2D patterns, deforms them to fit on a human, and applies stitching to sew those patterns together. Such work usually relies on labor work.In this thesis, we describe an approach to reconstruct clothes and human that both are from the same space. With multiple Kinects, it models the 3D clothes directly out of a dressed mannequin without the need of the predefined 2D clothes patterns, and fits them to a human user. Our approach has several advantages: (i) a simple hardware setting consisted of multiple Kinects to capture a human model; (ii) 3D clothes modeling directly out of captured human figure. To the best of our knowledge, our work is the first one which separates clothes out of captured human figure; (iii) resizing of clothes adapting to any sized human user; (iv) a novel idea of virtual try-on where clothes and human are captured in the same location.iii

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Section: Virtual Try-on In 3dmentioning

confidence: 99%

“…For the automatically 2D patterns to 3D clothes, the clothes was sewed from several deformed 2D patterns. And information of the technical details about deforming 2D patterns to the 3D mannequin were not described in most papers, such as [11] [12].…”

Section: Clothes Resizing For Virtual Try-onmentioning

confidence: 99%

Customized 3D Clothes Modeling for Virtual Try-on System based on Multiple Kinects

Huang

Lee

2016

Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications

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“…Humans are usually captured with clothing, that is, the actual (naked) human shape is concealed by the clothing and usually differs from the appearance. Virtual try-on systems, an important application of naked shapes, typically superimpose 3D models of clothing onto human shape [1]. Although it allows the consumer to visualize whether an item of clothing suits them with regard to design and color, it is difficult to determine how well the size of the item fits their actual body shape.…”

Section: Introductionmentioning

confidence: 99%

“…The proposed approach is built on a previous singleimage human 3D modeling method (SMPLify [5]), which *Correspondence: okura@am.sanken.osaka-u.ac.jp † Yui Shigeki and Fumio Okura contributed equally to this work. 1 The Institute of Scientific and Industrial Research, Osaka University, 8-1, Mihogaoka, Ibaraki, Osaka, Japan Full list of author information is available at the end of the article optimizes a parametric model of 3D human pose and shape [6] to fit joint positions acquired by a joint estimation method [7]. Joint-based optimization does capture aspects of shape information related to human skeletons such as the length of the arms and legs.…”

Section: Introductionmentioning

confidence: 99%

Estimating 3D human shape under clothing from a single RGB image

Shigeki

Okura

Mitsugami

et al. 2018

IPSJ T Comput Vis Appl

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Estimation of naked human shape is essential in several applications such as virtual try-on. We propose an approach that estimates naked human 3D pose and shape, including non-skeletal shape information such as musculature and fat distribution, from a single RGB image. The proposed approach optimizes a parametric 3D human model using person silhouettes with clothing category, and statistical displacement models between clothed and naked body shapes associated with each clothing category. Experiments demonstrate that our approach estimates human shape more accurately than a prior method.

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“…The state-of-the-art garment modeling approaches [41,50,51] emphasize on interactive editing of 2D pattern design and corresponding 3D drape. However, the ability to create a diverse set of 3D garments is required with the trend of online 3D model collections and rapid growth of mass apparel customization for virtual clothes try-on system [59]. Trying to address the content creation from the aspect of 3D garment modeling remains a challenging problem.…”

Section: Introductionmentioning

confidence: 99%

A data-driven editing framework for automatic 3D garment modeling

Liu

et al. 2016

Multimed Tools Appl

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Exploring shape variations on virtual garments is significant but challenging to the aspect of 3D garment modeling. In this paper, we propose a data-driven editing framework for automatic 3D garment modeling, which includes semantic garment segmentation, probabilistic reasoning for component suggestion, and garment component merging. The key idea in this work is to develop a simple but effective garment synthesis that utilizes a continuous style description, which can be characterized by the ratio of area and boundary length on garment components. First, a semi-supervised learning algorithm is proposed to simultaneously segment and label the components in 3D garments. Second, a set of matchable probability measurement is applied to recommend components that can be regarded as a new 3D garment. Third, a variation synthesis is developed to satisfy the garment style criteria while ensuring the realistic-looking plausibility of the results. As demonstrated by the experiments, our method is able to generate various reasonable garments with material effects to enrich existing 3D garments.

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A Mixed Reality Virtual Clothes Try-On System

Cited by 84 publications

References 27 publications

Customized 3D Clothes Modeling for Virtual Try-on System based on Multiple Kinects

Customized 3D Clothes Modeling for Virtual Try-on System based on Multiple Kinects

Estimating 3D human shape under clothing from a single RGB image

A data-driven editing framework for automatic 3D garment modeling

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