WO2016000304A1 - 一种虚拟试衣方法及虚拟试衣系统 - Google Patents

一种虚拟试衣方法及虚拟试衣系统 Download PDF

Info

Publication number
WO2016000304A1
WO2016000304A1 PCT/CN2014/085279 CN2014085279W WO2016000304A1 WO 2016000304 A1 WO2016000304 A1 WO 2016000304A1 CN 2014085279 W CN2014085279 W CN 2014085279W WO 2016000304 A1 WO2016000304 A1 WO 2016000304A1
Authority
WO
WIPO (PCT)
Prior art keywords
garment
size information
human body
sampler
tried
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Ceased
Application number
PCT/CN2014/085279
Other languages
English (en)
French (fr)
Inventor
牟鑫鑫
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
BOE Technology Group Co Ltd
Original Assignee
BOE Technology Group Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by BOE Technology Group Co Ltd filed Critical BOE Technology Group Co Ltd
Publication of WO2016000304A1 publication Critical patent/WO2016000304A1/zh
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

Links

Classifications

    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04NPICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N13/00Stereoscopic video systems; Multi-view video systems; Details thereof
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06QINFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00Commerce
    • GPHYSICS
    • G16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16ZINFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS, NOT OTHERWISE PROVIDED FOR
    • G16Z99/00Subject matter not provided for in other main groups of this subclass

Definitions

  • the present disclosure provides a virtual fitting method and a virtual fitting system for solving the problem that the existing network purchase clothing is difficult to visually view the clothing fitting effect.
  • an embodiment of the present disclosure provides a virtual fitting system, including: obtaining a human body image of a sampler through a depth camera;
  • the three-dimensional fitting image is displayed by a display unit.
  • the acquiring the three-dimensional model of the garment to be tested comprises:
  • the matching the body size information of the sampler with the size information of the garment to be tried on, and selecting the size of the adapted garment to be tested comprises:
  • the size information of the garment suitable for the wearer is matched with the size information of the garment to be tried by the merchant, and the size of the adapted garment to be tried is selected.
  • the step of determining the human body size information of the sampler according to the image of the human body of the sampler includes:
  • the human body size information of the fitter is determined based on the height information of the wearer externally input based on the height information of the fitter and the human body image of the fitter.
  • the step of determining the human body size information of the sampler according to the human body image :
  • the body size information of the fitter is determined based on the height information of the fitter and the human body image.
  • the obtaining the three-dimensional model of the garment to be tested according to the selected size comprises: selecting, in the clothing model database, a three-dimensional model of the garment that matches the style of the garment to be tried, according to the The size information of the garment to be tried and the selected three-dimensional model of the garment are generated to generate a three-dimensional model of the garment to be tested.
  • the body size information includes a shoulder width, a chest circumference, a waist circumference, a leg length, and/or an arm length.
  • a virtual fitting system comprising:
  • a depth camera for obtaining a human body image of the fitting person
  • a human body size information acquiring unit configured to determine the person of the fitting person according to the human body image Body size information
  • a three-dimensional modeling unit configured to create a human body three-dimensional sentence of the fitter according to the human body size information.
  • a garment model obtaining unit configured to obtain a three-dimensional model of the garment to be tried on
  • a fusion unit configured to fuse the three-dimensional model of the human body of the sampler with the three-dimensional model of the garment to be tested, to obtain a three-dimensional fitting image
  • the display unit, ⁇ displays the three-dimensional fitting image.
  • the clothing model obtaining unit is specifically configured to match body size information of the sampler with size information of the clothing to be tried, and select an adapted size of the clothing to be tried; according to the selected size Obtaining a three-dimensional model of the garment to be tried on.
  • the clothing model obtaining unit is specifically configured to calculate, according to the human body size information of the sampler and the pre-stored size error, size information suitable for the clothing worn by the sampler;
  • the size information of the clothing worn by the person is matched with the size information of the clothing to be tried by the merchant, and the size of the adapted clothing to be tried is obtained.
  • the human body size information acquiring unit is configured to obtain the input height information of the sampler, and determine, according to the height information of the sampler and the human body image of the sampler.
  • the human body size information acquiring unit is configured to acquire the placement height information of the depth camera, and calculate a horizontal distance of the sampler from the virtual fitting system according to the placement height information of the depth camera. Calculating height information of the sampler according to the horizontal distance and the placement height information of the depth camera, and determining the size of the human body of the sampler according to the height information of the sampler and the human body image information.
  • the virtual fitting system further includes:
  • a clothing model database for storing a three-dimensional model of a variety of styles of clothing
  • the clothing model obtaining unit is specifically configured to select, from the clothing model database, a three-dimensional model of the garment that matches the style of the garment to be tried, according to the size information of the garment to be tried and the selected three-dimensional model of the garment. , generating a three-dimensional model of the garment to be tried on.
  • the human body image acquired by the depth camera can easily create a three-dimensional model of the human body, and the person The three-dimensional model is merged with the three-dimensional model of the garment to be tested, and the three-dimensional fitting effect is visually seen.
  • FIG. 1 is a schematic flow chart of a virtual fitting method according to an embodiment of the present disclosure.
  • FIG. 2 is a schematic diagram of a method for calculating a human body height according to an embodiment of the present disclosure.
  • FIG. 3 is a schematic structural diagram of a virtual fitting system according to an embodiment of the present disclosure.
  • FIG. 1 is a schematic flowchart diagram of a virtual fitting method according to an embodiment of the present disclosure, where the method is applied to a virtual fitting system, and the virtual fitting system may have a display for a television, a personal computer, or the like.
  • the electronic device of the unit, the method comprising the steps of:
  • Step Si h obtains a human body image of the fitting person through the depth camera
  • the dresser can stand within the imaging range of the depth camera and smoothly turn around in a specified time (such as 10 seconds). Take the image processing speed at 30 Hz as an example. The camera can shoot 30 per second. The human body image, after turning 360 degrees, can get more than 300 images of people at different angles.
  • Step S12 determining body size information of the sampler according to the human body image; the body size information may include information such as shoulder width, chest circumference, waist circumference, leg length, and/or arm length.
  • Step S13 creating a three-dimensional model of the human body of the fitter according to the human body size information; and obtaining a three-dimensional model of the garment to be tried on;
  • Step merging the three-dimensional model of the human body of the sampler with the three-dimensional model of the garment to be tested, and obtaining a three-dimensional fitting image;
  • Step S16 displaying the three-dimensional fitting image by a display unit.
  • the human body image acquired by the depth camera can be conveniently
  • the three-dimensional model of the human body is created, and the three-dimensional model of the human body is merged with the three-dimensional model of the garment to be tested, and the three-dimensional fitting effect is visually seen.
  • Method 1 Determine the size information of the dresser by taking the height of the dresser as a reference.
  • the height information of the fitting device can be manually input by the fitting machine, and the virtual fitting system acquires the height information of the externally input fittings, and is determined according to the height information of the fitting person and the human body image of the fitting person.
  • Body size information of the sampler is other body size information other than height, such as leg length, chest circumference, waist circumference, and the like.
  • the ratio of the actual height of the fitting and the height of the human body image is calculated to be 5. If the leg length of the fitting obtained from the human body image is 21 cm, it can be estimated that the actual leg length of the fitting is 105 cm.
  • Method 2 Determine the size information of the fitter by using the placement height of the depth camera as a reference.
  • the determining, according to the human body image, the body size information of the sampler may include:
  • the body size information of the fitter is determined based on the height information of the fitter and the human body image.
  • the size information of the fitter can be easily obtained.
  • the above method is merely exemplified, and the principle is to find a reference object whose size is known or calculated, and to calculate the body size information as a standard.
  • the body size information of the sampler is not determined by other methods.
  • a clothing may have several code numbers, such as S code, M code, L code and XL code.
  • code numbers such as S code, M code, L code and XL code.
  • the size and size of different brands or types of clothing of the same code number may also be different, for example
  • the S code of some European and American style clothes may be equivalent to the M code of domestic clothing. Therefore, when selecting a certain clothing, 3 ⁇ 4 households may not be able to accurately select the appropriate code number to try on, and need to try on multiple times. Clothing with different code numbers.
  • step S14 (acquiring the three-dimensional model of the garment to be tried on) may specifically include: The size information is matched with the size information of the garment to be tested, the size of the adapted garment to be tested is selected, and the three-dimensional model of the garment to be tried is determined according to the size of the adapted garment to be tested. At this time, the fitter can select a three-dimensional model corresponding to the size of the garment to be tried that is recommended by the virtual fitting system.
  • the size information of the fitter is 36 cm, and the actual measured shoulder width of a suitable garment may require 38 cm. Therefore, assuming that al, bl, cl... are the determined body size information, a', b% c'... are the dimensional errors corresponding to al, bl, cl... respectively, then the size information of the final recommended clothing, A, B, C... is: A ⁇ al+a'
  • the size information of the fitter is matched with the size information of the garment to be tested, and the size of the adapted garment to be tested may specifically include: Determining the size information of the fitter and the pre-stored dimensional error, and calculating the size information of the garment suitable for the wearer; and then, the size information of the garment suitable for the wearer is compared with the offer provided by the merchant. The size information of the garment is matched, and the size of the garment to be tried that matches the fitter is obtained, and the cone is recommended for selection.
  • the size of the garment to be tried to match with the fitting person can be accurately recommended, and the experience of the fitting person can be improved.
  • the fitter can select a three-dimensional model of the garment to be tried by the virtual fitting system for virtual fitting.
  • the virtual fitting system of the embodiment of the present disclosure can also generate a three-dimensional pattern of the fitting garment, which will be specifically described below.
  • the virtual fitting system of the embodiment of the present disclosure may store a three-dimensional model of a plurality of styles of clothing in advance through a clothing model database. For example, a three-dimensional model of a variety of common styles of clothing is stored.
  • a three-dimensional model of the garment matching the style of the garment to be tried is selected in the clothing model database, according to the size information of the garment to be tried and the selected garment.
  • the three-dimensional model generates a three-dimensional model of the garment to be tried on.
  • the garment of the first yard or the small yard may be re-selected to regenerate the three-dimensional fitting image.
  • the human body three-dimensional model and the clothing model can be created according to the existing modeling method, and the three-dimensional model of the human body three-dimensional model and the clothing to be tried on can be merged according to the existing fusion method, and details are not described herein again.
  • FIG. 3 is a schematic structural diagram of a virtual fitting system according to an embodiment of the present disclosure.
  • the virtual fitting system may be an electronic device having a display unit such as a television or a personal computer, and the virtual fitting system includes:
  • the depth camera 3], ffi is used to obtain a human body image of the fitter; the depth camera 31 may be disposed at any position of the front bezel of the virtual fitting system.
  • the human body size information acquiring unit 32 is configured to determine body size information of the sampler according to the human body image
  • a three-dimensional modeling unit 33 configured to create a human body three-dimensional model of the fitter according to the human body size information
  • a garment model obtaining unit 34 configured to acquire a three-dimensional model of the garment to be tried on;
  • a fusion unit 35 configured to fuse the three-dimensional model of the human body of the sampler with the three-dimensional model of the garment to be tested, to obtain a three-dimensional fitting image
  • the display unit 36 is configured to display the three-dimensional fitting image.
  • the three-dimensional model of the human body can be conveniently created, and the three-dimensional model of the human body is merged with the three-dimensional model of the garment to be tested, and the three-dimensional fitting effect is visually seen.
  • the human body size information acquiring unit 32 may be specifically configured to obtain externally input height information of the sampler, and determine the height according to the height information of the sampler and the human body image of the sampler. The body size information of the tester is described.
  • the human body size information acquiring unit 32 is further configured to acquire the placement height information of the depth camera, and calculate the fitter distance from the virtual fitting system according to the placement height information of the depth camera. a horizontal distance, calculating height information of the sampler according to the horizontal distance and the placement height information of the depth camera, and determining the fitting according to the height information of the sampler and the human body image Body size information.
  • the human body size information obtaining unit 32 can conveniently obtain the human body size of the sampler.
  • the clothing model obtaining unit 34 of the embodiment of the present disclosure can be specifically used to provide the size information of the sampler and the merchant. The size information of the garment to be tested is matched, the size of the garment to be tried that matches the fitting person is obtained, and a recommendation is made for selection.
  • the clothing model obtaining unit 34 of the embodiment of the present disclosure may further be specifically used according to the The size information of the fitter and the pre-stored size error are calculated, and the size information of the garment suitable for the wearer is calculated; the size information of the garment suitable for the wearer and the size of the garment to be tried by the merchant are The information is matched, the size of the garment to be tried that matches the fitter is obtained, and a recommendation is made for selection.
  • the garment model obtaining unit may specifically obtain a three-dimensional model of the garment to be tried by the merchant.
  • the virtual fitting system of the embodiment of the present disclosure may further include: a clothing model database for storing a three-dimensional model of a plurality of styles of clothing; and when the merchant does not provide a three-dimensional model of the clothing to be tried, the clothing model acquiring unit is specifically used Selecting a three-dimensional model of the garment matching the style of the garment to be tried on, and generating the garment to be tried on the basis of the size information of the garment to be tested and the selected three-dimensional model of the garment. 3D model.

Landscapes

  • Business, Economics & Management (AREA)
  • Engineering & Computer Science (AREA)
  • Marketing (AREA)
  • Strategic Management (AREA)
  • Accounting & Taxation (AREA)
  • Development Economics (AREA)
  • Economics (AREA)
  • Finance (AREA)
  • Multimedia (AREA)
  • Signal Processing (AREA)
  • Physics & Mathematics (AREA)
  • General Business, Economics & Management (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Processing Or Creating Images (AREA)
  • Image Processing (AREA)

Abstract

本公开提供一种虚拟试衣方法及虚拟试衣系统,该虚拟试衣方法包括:通过深度摄像头获取试衣者的人体图像;根据所述人体图像,确定所述试衣者的人体尺寸信息;根据所述人体尺寸信息创建所述试衣者的人体三维模型;获取选择的待试穿服装的三维模型;将所述试衣者的人体三维模型与待试穿服装的三维模型进行融合,得到三维试衣图像;通过显示单元显示所述三维试衣图像。

Description

本申请主张在 2014 年 06 月 30 日在中国提交的中国专利申请号 No. 201410307799.9的优先权, 其全部内容通过引用包含于此。
Figure imgf000003_0001
随着网络科技的不断发展, 许多消费者喜欢通过网络购买服装。 目前, 消费者通常只能通过网络上的照片或参考模特所穿服装的效果选择服装。 这 种购买方式使得消费者无法看到自己试穿服装的效果, 丛而导致消费者很难 通过网络买到满意的服装。
有鉴于此, 本公开提供一种虚拟试衣方法及虛拟试衣系统, 用以解决现 有的网络购买服装的方式难以直观地查看服装试穿效果的问题。
为解决上述技术问题, 本公开的实施例提供一种虚拟试衣系统, 包括: 通过深度摄像头获取试衣者的人体图像;
根据所述试衣者的人体图像, 确定所述试衣者的人体尺寸信息; 根据所述人体尺寸信息创建所述试衣者的人体三维模型;
获取待试穿服装的三维模型;
将所述试衣者的人体三维模型与待试穿服装的三维模型进行融合, 得到 三维试衣图像;
通过显示单元显示所述三维试衣图像。
可选地, 所述获取待试穿服装的三维模型具体包括:
将所述试衣者的人体尺寸信息与待试穿服装的尺寸信息进行匹配, 选择 适配的待试穿服装的尺码;
根据选择的尺码获取所述待试穿服装的三维模型。
可选地, 所述将所述试衣者的人体尺寸信息与待试穿服装的尺寸信息进 行匹配, 选择适配的待试穿服装的尺码具体包括:
根据所述试衣者的人体尺寸信息以及预存的尺寸误差, 计算适合所述试 衣者穿着的服装的尺寸信息;
将适合所述试衣者穿着的服装的尺寸信息与商家提供的待试穿服装的尺 寸信息进行匹配, 选择适配的待试穿服装的尺码。
可选地, 所述根据所述试衣者的人体图像, 确定所述试衣者的人体尺寸 信息的步骤具体包括:
根据外部输入的所述试衣者的身高信息, 根据所述试衣者的身高信息及 所述试衣者的人体图像, 确定所述试衣者的人体尺寸信息。
可选地, 所述根据所述人体图像, 确定所述试衣者的人体尺寸信息的步 骤呉体 Έϊίΐ:
获取所述深度摄像头的放置高度信息;
根据所述深度摄像头的放置高度信息, 计算所述试衣者距离所述虛拟试 衣系统的水平距离;
根据所述水平距离及所述深度摄像头的放置高度信息, 计算所述试衣者 的身高信息;
根据所述试衣者的身高信息及所述人体图像, 确定所述试衣者的人体尺 寸信息。
可选地,所述根据选择的尺码获取所述待试穿服装的三维模型具体包括: 丛所述服装模型数据库中选择与所述待试穿服装的款式相匹配的服装三 维模型, 根据所述待试穿服装的尺寸信息及选择的服装三维模型, 生成所述 待试穿服装的三维模型。
可选地, 所述人体尺寸信息包括肩宽、 胸围、 腰围、 腿长和 /或手臂长。 本公开还提供一种虛拟试衣系统, 包括:
深度摄像头, 用于获取试衣者的人体图像;
人体尺寸信息获取单元, 用于根据所述人体图像, 确定所述试衣者的人 体尺寸信息;
三维建模单元, 用于根据所述人体尺寸信息创建所述试衣者的人体三维 刑。
服装模型获取单元, 用于获取待试穿服装的三维模型;
融合单元, 用于将所述试衣者的人体三维模型与待试穿服装的三维模型 进行融合, 得到三维试衣图像;
显示单元, ^于显示所述三维试衣图像。
可选地, 所述服装模型获取单元, 具体用于将所述试衣者的人体尺寸信 息与待试穿服装的尺寸信息进行匹配, 选择适配的待试穿服装的尺码; 根据 选择的尺码获取所述待试穿服装的三维模型。
可选地, 所述服装模型获取单元, 具体用于根据所述试衣者的人体尺寸 信息以及预存的尺寸误差, 计算适合所述试衣者穿着的服装的尺寸信息; 将 适合所述试衣者穿着的服装的尺寸信息与商家提供的待试穿服装的尺寸信息 进行匹配, 获取适配的待试穿服装的尺码。
可选地, 所述人体尺寸信息获取单元, 具体) ¾于获取输入的所述试衣者 的身高信息, 根据所述试衣者的身高信息及所述试衣者的人体图像, 确定所 可选地, 所述人体尺寸信息获取单元, 具体 于获取所述深度摄像头的 放置高度信息, 根据所述深度摄像头的放置高度信息, 计算所述试衣者距离 所述虚拟试衣系统的水平距离, 根据所述水平距离及所述深度摄像头的放置 高度信息, 计算所述试衣者的身高信息, 并根据所述试衣者的身高信息及所 述人体图像, 确定所述试衣者的人体尺寸信息。
可选地, 所述虚拟试衣系统还包括:
服装模型数据库, 用于存储多种款式的服装的三维模型;
其中, 服装模型获取单元, 具体用于从所述服装模型数据库中选择与所 述待试穿服装的款式相匹配的服装三维模型, 根据所述待试穿服装的尺寸信 息及选择的服装三维模型, 生成所述待试穿服装的三维模型。
本公开的上述技术方案的有益效果如下:
可以通过深度摄像头获取的人体图像方便地创建人体三维模型, 并将人 体三维模型与待试穿服装的三维模型进行融合, 直观地看到三维试衣效果。 此外, 还可以根据试衣者的人体尺寸信息, 准确地向试衣者推荐与其匹配的 待试穿服装的尺码, 提高了试衣者的体验。
图 1为本公开实施例的虚拟试衣方法的流程示意图。
图 2为本公开实施例的人体身高的计算方法的示意图。
图 3为本公开实施例的虚拟试衣系统的结构示意图。
为使本公开要解决的技术问题、 技术方案和优点更加清楚, 下面将结合 附图及具体实施例进行详细描述。
请参考图 1, 图 1 为本公开实施例的虚拟试衣方法的流程示意图, 所述 方法应) ¾于一虚拟试衣系统, 所述虚拟试衣系统可以为电视机、 个人计算机 等具有显示单元的电子设备, 所述方法包括以下步骤:
步骤 Si h 通过深度摄像头获取试衣者的人体图像;
具体操作时, 试衣者可以站立在深度摄像头的摄像范围内, 在规定的时 间内 (如 10秒) 平稳地转身一圈, 以 30赫兹频率的图像处理速度为例, 摄 像头每秒可以拍摄 30幅人体图像,转身 360度后可获得 300多幅不同角度的 人图图像。
步骤 S12: 根据所述人体图像, 确定所述试衣者的人体尺寸信息; 所述人体尺寸信息可以包括肩宽、胸围、腰围、腿长和 /或手臂长等信息。 步骤 S13 : 根据所述人体尺寸信息创建所述试衣者的人体三维模型; 步骤 获取待试穿服装的三维模型;
步骤 将所述试衣者的人体三维模型与待试穿服装的三维模型进行 融合, 得到三维试衣图像;
歩骤 S16: 通过显示单元显示所述三维试衣图像。
通过上述实施例提供的方法, 可以通过深度摄像头获取的人体图像方便 地创建人体三维模型,并将人体三维模型与待试穿服装的三维模型进行融合, 直观地看到三维试衣效果。
下面对如何根据所述人体图像, 确定所述试衣者的人体尺寸信息的方法 进行详细说明。
方法一: 以试衣者的身高为参考物, 确定试衣者的人体尺寸信息。
具体的, 可以由试衣者手动输入的其身高信息, 虚拟试衣系统获取外部 输入的试衣者的身高信息, 根据所述试衣者的身高信息及所述试衣者的人体 图像, 确定所述试衣者的人体尺寸信息。 所述人体尺寸信息为除身高之外的 其他人体尺寸信息, 如腿长、 胸围、 腰围等。
举例来说, 试衣者的身高为 170cm, 从人体图像中获取的试衣者的身高 为 34cm, 则计算出试衣者的实际身高与人体图像中的身高的比例系数为 5。 假如从人体图像中获取的试衣者的腿长为 21cm,则可以估算出试衣者的实际 腿长为 105cm。
方法二: 以深度摄像头的放置高度为参考物, 确定试衣者的人体尺寸信 息。
具体的, 所述根据所述人体图像, 确定所述试衣者的人体尺寸信息的歩 骤可以包括;
获取所述深度摄像头的放置高度信息;
根据所述深度摄像头的放置高度信息, 计算所述试衣者距离所述虚拟试 衣系统的水平距离;
根据所述水平距离及所述深度摄像头的放置高度信息, 计算所述试衣者 的身 ι,ϋ ;
根据所述试衣者的身高信息及所述人体图像, 确定所述试衣者的人体尺 寸信息。
举例来说, 如图 2所示, 假设虚拟试衣系统为一电视机, 电视机距放置 平台的高度为 hi (深度摄像头设置在电视机的上边框上, 即深度摄像头距放 置平台的高度也是 hl ), 放置电视机的平台的髙度为 h2 , 则可得出深度摄像 头的放置髙度 H=hl+h2, 或者, 也可以直接测量深度摄像头的放置高度 H, 试衣者可将深度摄像头的放置髙度 H手动输入虚拟试衣系统。 假设深度摄像头竖直方向的识别角度为 a, 根据所述识别角度 a, 可什算 出图 2 中的夹角 c=90°- a/2, 从而可计算出试衣者距离电视机的水平距离 S= H*tan (90。- a/2)。
假设试衣者的身高为 H' (H'>H), tan b/2- (Η' H) /S, 则可计算出试衣 者的身高 H'二 H+S* ian b/2 , 即: H'-hi+h2+ S* tan b/2。
当试衣者的身高 H'<H时, 什算过程相类似, 在此不再赘述。
当然, 上述两种方法中, 在进行人体图像摄取时, 试衣者站立的位置需 要保证深度摄像头能够摄取到人体的全身图像。
通过上述方法, 可以方便地获取试衣者的人体尺寸信息。
上述方法仅作举例说明, 原理在于, 找到尺寸已知或经过计算后已知的 参照物, 以此为标准计算出人体尺寸信息。 当然, 本公开实施例中, 也不排 除通过其他方法确定所述试衣者的人体尺寸信息。
通常情况下, 一种服装可能会有好几个码号, 如 S码、 M码、 L码和 XL 码等, 另外, 同种码号的不同品牌或类型的服装的大小尺寸也可能不同, 例 如, 有些欧美款式的衣服的 S码可能相当于国内服装的 M码, 因而, )¾户在 选择某个服装时, 可能无法准确地选择合适的码号进行试穿, 丛而需要多次 试穿不同码号的服装。
本公开实施例中, 为解决试衣者无法准确地选择合适的服装码号进行试 穿的问题, 步骤 S14 (获取待试穿服装的三维模型) 可以具体包括: 将所述 试衣者的人体尺寸信息与待试穿服装的尺寸信息进行匹配, 选择适配的待试 穿服装的尺码, 并根据适配的待试穿服装的尺码, 确定待试穿服装的三维模 型。 此时, 试衣者可以选择虚拟试衣系统推荐的与试衣者适配的待试穿服装 的尺码对应的三维模型。
试衣者的人体尺寸信息通过与实际的服装尺寸之间存在一定的误差, 例 如, 人体的实际肩宽为 36cm, 而穿着合适的服装的实际测量肩宽可能需要 38cm。 因而, 假定 al, bl, cl…为确定的人体尺寸信息, a', b% c'…分别 为 al , bl, cl…对应的尺寸误差,则最终推荐的服装的尺寸信息, A, B, C...... 为: A^al+a'
B-bl+b'
Ocl+c, 因而, 本公开实施例中, 将所述试衣者的人体尺寸信息与待试穿服装的 尺寸信息进行匹配, 选择适配的待试穿服装的尺码可以具体包括: 首先根据 所述试衣者的人体尺寸信息以及预存的尺寸误差, 计算适合所述试衣者穿着 的服装的尺寸信息; 然后, 将适合所述试衣者穿着的服装的尺寸信息与商家 提供的待试穿服装的尺寸信息进行匹配, 获取与所述试衣者匹配的待试穿服 装的尺码, 并进行锥荐以供选择。
通过上述方法,可以准确地向试衣者推荐与其匹配的待试穿服装的尺码, 提高了试衣者的体验。
当商家提供待试穿服装的三维模型时, 试衣者可以选择虚拟试衣系统推 荐的待试穿的服装的三维模型进行虚拟试衣。
当商家不提供试穿服装的三维模式时, 本公开实施例的虚拟试衣系统也 可以生成试穿服装的三维模式, 下面将具体说明。
具体的, 本公开实施例的虚拟试衣系统可以预先通过一服装模型数据库 存储多种款式的服装的三维模型。 例如存储常见的各种款式的服装的三维模 型。
当需要生成待试穿服装的三维模型时, 丛所述服装模型数据库中选择与 所述待试穿服装的款式相匹配的服装三维模型, 根据所述待试穿服装的尺寸 信息及选择的服装三维模型, 生成所述待试穿服装的三维模型。
此外, 本公开实施例中, 如果试衣者对显示的三维试衣图像中的服装的 试穿效果并不满意, 可以重新选择大一码或小一码的服装, 重新生成三维试 衣图像。
上述实施例中,可以按照现有的建模方式创建人体三维模型和服装模型, 也可以按照现有的融合方法进行人体三维模型和待试穿服装的三维模型的融 合, 在此不再赘述。
请参考图 3 , 图 3为本公开实施例的虛拟试衣系统的结构示意图, 所述 虚拟试衣系统可以为电视机、 个人计算机等具有显示单元的电子设备, 所述 虛拟试衣系统包括:
深度摄像头 3】, ffi于获取试衣者的人体图像; 所述深度摄像头 31 可设 置于所述虚拟试衣系统的前边框的任意位置处。
人体尺寸信息获取单元 32, 用于根据所述人体图像, 确定所述试衣者的 人体尺寸信息;
三维建模单元 33, 用于根据所述人体尺寸信息创建所述试衣者的人体三 维模型;
服装模型获取单元 34, 用于获取待试穿服装的三维模型;
融合单元 35, 用于将所述试衣者的人体三维模型与待试穿服装的三维模 型进行融合, 得到三维试衣图像;
显示单元 36, 用于显示所述三维试衣图像。
通过上述实施例提供的虚拟试衣系统, 可以方便地创建人体三维模型, 并将人体三维模型与待试穿服装的三维模型进行融合, 直观地看到三维试衣 效果。
可选的,所述人体尺寸信息获取单元 32可以具体用于获取外部输入的所 述试衣者的身高信息,根据所述试衣者的身高信息及所述试衣者的人体图像, 确定所述试衣者的人体尺寸信息。
可选的,所述人体尺寸信息获取单元 32还可以具体用于获取所述深度摄 像头的放置高度信息, 根据所述深度摄像头的放置高度信息, 计算所述试衣 者距离所述虚拟试衣系统的水平距离, 根据所述水平距离及所述深度摄像头 的放置高度信息, 计算所述试衣者的身高信息, 并根据所述试衣者的身高信 息及所述人体图像, 确定所述试衣者的人体尺寸信息。
通过上述人体尺寸信息获取单元 32 可以方便地获取试衣者的人体尺寸 可选地,本公开实施例的服装模型获取单元 34可以具体用于将所述试衣 者的人体尺寸信息与商家提供的待试穿服装的尺寸信息进行匹配, 获取与所 述试衣者匹配的待试穿服装的尺码, 并进行推荐以供选择。
可选地,本公开实施例的服装模型获取单元 34还可以具体用于根据所述 试衣者的人体尺寸信息以及预存的尺寸误差, 计算适合所述试衣者穿着的服 装的尺寸信息; 将适合所述试衣者穿着的服装的尺寸信息与商家提供的待试 穿服装的尺寸信息进行匹配, 获取与所述试衣者匹配的待试穿服装的尺码, 并进行推荐以供选择。
通过上述服装推荐单元, 可以准确地向试衣者推荐与其匹配的待试穿服 装的尺码, 提高了试衣者的体验。
当商家提供待试穿服装的三维模型时, 所述服装模型获取单元可以具体 ffi于获取商家提供的待试穿服装的三维模型。
本公开实施例的虚拟试衣系统还可以包括: 服装模型数据库, 用于存储 多种款式的服装的三维模型; 当商家不提供待试穿服装的三维模型时, 所述 服装模型获取单元具体用于从所述服装模型数据库中选择与所述待试穿服装 的款式相匹配的服装三维模型, 根据所述待试穿服装的尺寸信息及选择的服 装三维模型, 生成所述待试穿服装的三维模型。
以上所述是本公开的可选实施方式, 应当指出, 对于本技术领域的普通 技术人员来说, 在不脱离本公开所述原理的前提下, 还可以作出若千改进和 润饰, 这些改进和润饰也应视为本公开的保护范围。

Claims

1 . 一种虚拟试衣方法, 包括:
通过深度摄像头获取试衣者的人体图像;
根据所述试衣者的人体图像, 确定所述试衣者的人体尺寸信息; 根据所述人体尺寸信息创建所述试衣者的人体三维模型;
获取待试穿服装的三维模型;
将所述试衣者的人体三维模型与待试穿服装的三维模型进行融合, 得到 三维试衣图像;
通过显示单元显示所述三维试衣图像。
2. 根据权利要求 1所述的虛拟试衣方法, 其中, 所述获取待试穿服装的 三维模型具体包括:
将所述试衣者的人体尺寸信息与待试穿服装的尺寸信息进行匹配, 选择 适配的待试穿服装的尺码;
根据选择的尺码获取所述待试穿服装的三维模型。
3. 根据权利要求 2所述的虚拟试衣方法, 其中, 所述将所述试衣者的人 体尺寸信息与待试穿服装的尺寸信息进行匹配, 选择适配的待试穿服装的尺 码具体包括:
根据所述试衣者的人体尺寸信息以及预存的尺寸误差, 计算适合所述试 衣者穿着的服装的尺寸信息;
将适合所述试衣者穿着的服装的尺寸信息与商家提供的待试穿服装的尺 寸信息进行匹配, 选择适配的待试穿服装的尺码。
4. 根据权利要求 1所述的虛拟试衣方法, 其中, 所述根据所述试衣者的 人体图像, 确定所述试衣者的人体尺寸信息的歩骤具体包括:
获取外部输入的所述试衣者的身高信息, 根据所述试衣者的身高信息及 所述试衣者的人体图像, 确定所述试衣者的人体尺寸信息。
5. 根据权利要求 1所述的虛拟试衣方法,其中,所述根据所述人体图像, 确定所述试衣者的人体尺寸信息的步骤具体包括:
获取所述深度摄像头的放置高度信息; 根据所述深度摄像头的放置高度信息, 计算所述试衣者距离所述虚拟试 衣系统的水平距离;
根据所述水平距离及所述深度摄像头的放置高度信息, 计算所述试衣者 的身高信息;
根据所述试衣者的身高信息及所述人体图像, 确定所述试衣者的人体尺 寸信息。
6. 根据权利要求 2所述的虛拟试衣方法, 其中, 所述根据选择的尺码获 取所述待试穿服装的三维模型具体包括:
从所述服装模型数据库中选择与所述待试穿服装的款式相匹配的服装三 维模型, 根据所述待试穿服装的尺寸信息及选择的服装三维模型, 生成所述 待试穿服装的三维模型。
7. 根据权利要求 1 6任一项所述的虚拟试衣方法, 其特征在于, 所述人 体尺寸信息包括肩宽、 胸围、 腰围、 腿长和 /或手臂长。
8. 一种虚拟试衣系统, 包括:
深度摄像头, 用于获取试衣者的人体图像;
人体尺寸信息获取单元, 用于根据所述人体图像, 确定所述试衣者的人 体尺寸信息;
三维建模单元, 用于根据所述人体尺寸信息创建所述试衣者的人体三维 mm .
服装模型获取单元, 用于获取待试穿服装的三维模型;
融合单元, 用于将所述试衣者的人体三维模型与待试穿服装的三维模型 进行融合, 得到三维试衣图像;
显示单元, )¾于显示所述三维试衣图像。
9. 根据权利要求 8所述的虚拟试衣系统,其中,所述服装模型获取单元, 具体用于将所述试衣者的人体尺寸信息与待试穿服装的尺寸信息进行匹配, 选择适配的待试穿服装的尺码; 根据选择的尺码获取所述待试穿服装的三维 模型。
10. 根据权利要求 9 所述的虚拟试衣系统, 其中, 所述服装模型获取单 元, 具体用于根据所述试衣者的人体尺寸信息以及预存的尺寸误差, 计算适 合所述试衣者穿着的服装的尺寸信息; 将适合所述试衣者穿着的服装的尺寸 信息与商家提供的待试穿服装的尺寸信息进行匹配, 获取适配的待试穿服装 的尺码。
11 . 根据权利要求 9所述的虚拟试衣系统, 其中, 还包括:
服装模型数据库, 用于存储多种款式的服装的三维模型;
其中, 服装模型获取单元, 具体用于从所述服装模型数据库中选择与所 述待试穿服装的款式相匹配的服装三维模型, 根据所述待试穿服装的尺寸信 息及选择的服装三维模型, 生成所述待试穿服装的三维模型。
12. 根据权利要求 8所述的虛拟试衣系统, 其中, 所述人体尺寸信息获 取单元, 具体 ffi于获取外部输入的所述试衣者的身高信息, 根据所述试衣者 的身高信息及所述试衣者的人体图像, 确定所述试衣者的人体尺寸信息。
13. 根据权利要求 8 所述的虚拟试衣系统, 其中, 所述人体尺寸信息获 取单元, 具体) ¾于获取所述深度摄像头的放置高度信息, 根据所述深度摄像 头的放置高度信息, 计算所述试衣者距离所述虚拟试衣系统的水平距离, 根 据所述水平距离及所述深度摄像头的放置高度信息, 计算所述试衣者的身高 信息, 并根据所述试衣者的身高信息及所述人体图像, 确定所述试衣者的人 体尺寸信息。
14. 根据权利要求 8- 13所述的虚拟试衣系统, 其中, 所述人体尺寸信息 包括肩宽、 胸围、 腰围、 腿长和 /或手臂长。
PCT/CN2014/085279 2014-06-30 2014-08-27 一种虚拟试衣方法及虚拟试衣系统 Ceased WO2016000304A1 (zh)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN201410307799.9 2014-06-30
CN201410307799.9A CN104091269A (zh) 2014-06-30 2014-06-30 一种虚拟试衣方法及虚拟试衣系统

Publications (1)

Publication Number Publication Date
WO2016000304A1 true WO2016000304A1 (zh) 2016-01-07

Family

ID=51638984

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2014/085279 Ceased WO2016000304A1 (zh) 2014-06-30 2014-08-27 一种虚拟试衣方法及虚拟试衣系统

Country Status (2)

Country Link
CN (1) CN104091269A (zh)
WO (1) WO2016000304A1 (zh)

Cited By (53)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2017069958A2 (en) 2015-10-09 2017-04-27 The Brigham And Women's Hospital, Inc. Modulation of novel immune checkpoint targets
WO2017087708A1 (en) 2015-11-19 2017-05-26 The Brigham And Women's Hospital, Inc. Lymphocyte antigen cd5-like (cd5l)-interleukin 12b (p40) heterodimers in immunity
WO2018049025A2 (en) 2016-09-07 2018-03-15 The Broad Institute Inc. Compositions and methods for evaluating and modulating immune responses
WO2018067991A1 (en) 2016-10-07 2018-04-12 The Brigham And Women's Hospital, Inc. Modulation of novel immune checkpoint targets
WO2018191553A1 (en) 2017-04-12 2018-10-18 Massachusetts Eye And Ear Infirmary Tumor signature for metastasis, compositions of matter methods of use thereof
WO2019070755A1 (en) 2017-10-02 2019-04-11 The Broad Institute, Inc. METHODS AND COMPOSITIONS FOR DETECTING AND MODULATING A GENETIC SIGNATURE OF IMMUNOTHERAPY RESISTANCE IN CANCER
WO2019094983A1 (en) 2017-11-13 2019-05-16 The Broad Institute, Inc. Methods and compositions for treating cancer by targeting the clec2d-klrb1 pathway
EP3569244A1 (en) 2015-09-23 2019-11-20 CytoImmune Therapeutics, LLC Flt3 directed car cells for immunotherapy
WO2019232542A2 (en) 2018-06-01 2019-12-05 Massachusetts Institute Of Technology Methods and compositions for detecting and modulating microenvironment gene signatures from the csf of metastasis patients
WO2020072700A1 (en) 2018-10-02 2020-04-09 Dana-Farber Cancer Institute, Inc. Hla single allele lines
WO2020081730A2 (en) 2018-10-16 2020-04-23 Massachusetts Institute Of Technology Methods and compositions for modulating microenvironment
WO2020131586A2 (en) 2018-12-17 2020-06-25 The Broad Institute, Inc. Methods for identifying neoantigens
WO2020186101A1 (en) 2019-03-12 2020-09-17 The Broad Institute, Inc. Detection means, compositions and methods for modulating synovial sarcoma cells
WO2020191079A1 (en) 2019-03-18 2020-09-24 The Broad Institute, Inc. Compositions and methods for modulating metabolic regulators of t cell pathogenicity
WO2020236967A1 (en) 2019-05-20 2020-11-26 The Broad Institute, Inc. Random crispr-cas deletion mutant
WO2020243371A1 (en) 2019-05-28 2020-12-03 Massachusetts Institute Of Technology Methods and compositions for modulating immune responses
WO2021030627A1 (en) 2019-08-13 2021-02-18 The General Hospital Corporation Methods for predicting outcomes of checkpoint inhibition and treatment thereof
WO2021041922A1 (en) 2019-08-30 2021-03-04 The Broad Institute, Inc. Crispr-associated mu transposase systems
CN112884638A (zh) * 2021-02-02 2021-06-01 北京东方国信科技股份有限公司 虚拟试衣方法及装置
WO2021212069A1 (en) 2020-04-17 2021-10-21 City Of Hope Flt3-targeted chimeric antigen receptor modified cells for treatment of flt3-positive malignancies
US11180730B2 (en) 2015-10-28 2021-11-23 The Broad Institute, Inc. Compositions and methods for evaluating and modulating immune responses by detecting and targeting GATA3
US11186825B2 (en) 2015-10-28 2021-11-30 The Broad Institute, Inc. Compositions and methods for evaluating and modulating immune responses by detecting and targeting POU2AF1
EP3867855A4 (en) * 2018-10-19 2021-12-15 Perfitly, LLC. PERFITLY AR / VR PLATFORM
CN114663199A (zh) * 2022-05-17 2022-06-24 武汉纺织大学 一种动态展示的实时三维虚拟试衣系统及方法
CN115661354A (zh) * 2022-11-07 2023-01-31 深圳市十二篮服饰有限公司 一种3d智能试衣模型系统
US11732257B2 (en) 2017-10-23 2023-08-22 Massachusetts Institute Of Technology Single cell sequencing libraries of genomic transcript regions of interest in proximity to barcodes, and genotyping of said libraries
US11739156B2 (en) 2019-01-06 2023-08-29 The Broad Institute, Inc. Massachusetts Institute of Technology Methods and compositions for overcoming immunosuppression
US11793787B2 (en) 2019-10-07 2023-10-24 The Broad Institute, Inc. Methods and compositions for enhancing anti-tumor immunity by targeting steroidogenesis
US11844800B2 (en) 2019-10-30 2023-12-19 Massachusetts Institute Of Technology Methods and compositions for predicting and preventing relapse of acute lymphoblastic leukemia
US11897953B2 (en) 2017-06-14 2024-02-13 The Broad Institute, Inc. Compositions and methods targeting complement component 3 for inhibiting tumor growth
US11913075B2 (en) 2017-04-01 2024-02-27 The Broad Institute, Inc. Methods and compositions for detecting and modulating an immunotherapy resistance gene signature in cancer
WO2024077256A1 (en) 2022-10-07 2024-04-11 The General Hospital Corporation Methods and compositions for high-throughput discovery ofpeptide-mhc targeting binding proteins
US11957695B2 (en) 2018-04-26 2024-04-16 The Broad Institute, Inc. Methods and compositions targeting glucocorticoid signaling for modulating immune responses
US11963966B2 (en) 2017-03-31 2024-04-23 Dana-Farber Cancer Institute, Inc. Compositions and methods for treating ovarian tumors
US11981922B2 (en) 2019-10-03 2024-05-14 Dana-Farber Cancer Institute, Inc. Methods and compositions for the modulation of cell interactions and signaling in the tumor microenvironment
US11994512B2 (en) 2018-01-04 2024-05-28 Massachusetts Institute Of Technology Single-cell genomic methods to generate ex vivo cell systems that recapitulate in vivo biology with improved fidelity
WO2024124044A1 (en) 2022-12-07 2024-06-13 The Brigham And Women’S Hospital, Inc. Compositions and methods targeting sat1 for enhancing anti¬ tumor immunity during tumor progression
US12036240B2 (en) 2018-06-14 2024-07-16 The Broad Institute, Inc. Compositions and methods targeting complement component 3 for inhibiting tumor growth
US12049643B2 (en) 2017-07-14 2024-07-30 The Broad Institute, Inc. Methods and compositions for modulating cytotoxic lymphocyte activity
US12165747B2 (en) 2020-01-23 2024-12-10 The Broad Institute, Inc. Molecular spatial mapping of metastatic tumor microenvironment
US12171783B2 (en) 2017-11-13 2024-12-24 The Broad Institute, Inc. Methods and compositions for targeting developmental and oncogenic programs in H3K27M gliomas
US12195725B2 (en) 2019-10-03 2025-01-14 Dana-Farber Cancer Institute, Inc. Compositions and methods for modulating and detecting tissue specific TH17 cell pathogenicity
EP4495246A2 (en) 2018-03-01 2025-01-22 University of Kansas Techniques for generating cell-based therapeutics using recombinant t cell receptor genes
US12226479B2 (en) 2017-05-11 2025-02-18 The General Hospital Corporation Methods and compositions of use of CD8+ tumor infiltrating lymphocyte subtypes and gene signatures thereof
US12227578B2 (en) 2016-11-11 2025-02-18 The Broad Institute, Inc. Modulation of intestinal epithelial cell differentiation, maintenance and/or function through T cell action
WO2025059533A1 (en) 2023-09-13 2025-03-20 The Broad Institute, Inc. Crispr enzymes and systems
US12271969B2 (en) 2020-05-15 2025-04-08 3M Innovative Properties Company Personal protective equipment training system with user-specific augmented reality content construction and rendering
WO2025097055A2 (en) 2023-11-02 2025-05-08 The Broad Institute, Inc. Compositions and methods of use of t cells in immunotherapy
US12297426B2 (en) 2019-10-01 2025-05-13 The Broad Institute, Inc. DNA damage response signature guided rational design of CRISPR-based systems and therapies
WO2025117544A1 (en) 2023-11-29 2025-06-05 The Broad Institute, Inc. Engineered omega guide molecule and iscb compositions, systems, and methods of use thereof
US12394502B2 (en) 2019-10-02 2025-08-19 The General Hospital Corporation Method for predicting HLA-binding peptides using protein structural features
US12421557B2 (en) 2019-08-16 2025-09-23 The Broad Institute, Inc. Methods for predicting outcomes and treating colorectal cancer using a cell atlas
US12590288B2 (en) 2017-04-12 2026-03-31 The Broad Institute, Inc. Method of treating an inflammatory disease by administering an agent which binds a surface receptor on a tuft cell that induces an ILC class 2 inflammatory response

Families Citing this family (52)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104318000A (zh) * 2014-10-17 2015-01-28 上海和鹰机电科技股份有限公司 一种成衣的自动生成方法
US9928412B2 (en) * 2014-10-17 2018-03-27 Ebay Inc. Method, medium, and system for fast 3D model fitting and anthropometrics
KR102240302B1 (ko) * 2014-10-21 2021-04-14 삼성전자주식회사 가상 피팅 장치 및 이의 가상 피팅 방법
CN104484813A (zh) * 2014-11-19 2015-04-01 李俊丽 一种云计算鞋服饰尺码比对系统及其比对方法
CN105608238A (zh) * 2014-11-21 2016-05-25 中兴通讯股份有限公司 服装试穿方法及装置
CN104637083A (zh) * 2015-01-29 2015-05-20 吴宇晖 一种虚拟试衣系统
CN106372318A (zh) * 2015-02-01 2017-02-01 陈赛 一种用于电子试衣系统的人体模型获取方法
WO2016123769A1 (zh) * 2015-02-05 2016-08-11 周谆 虚拟饰品试戴的人机交互方法和系统
CN106033463A (zh) * 2015-03-19 2016-10-19 阿里巴巴集团控股有限公司 对象展示方法及装置
CN104835055A (zh) * 2015-03-25 2015-08-12 深圳市百特文科技有限公司 通过二维码将服装数据与用户身材数据做比较并提示相应比对结果的方法、系统及设置
CN104851024A (zh) * 2015-05-08 2015-08-19 华侨大学 网络试衣系统
WO2016179819A1 (zh) * 2015-05-14 2016-11-17 周谆 手部虚拟饰品试戴的人机交互方法和系统
CN104820498B (zh) * 2015-05-14 2018-05-08 周谆 手部虚拟饰品试戴的人机交互方法和系统
CN105141944B (zh) * 2015-09-10 2017-07-04 相汇网络科技(杭州)有限公司 一种多维立体成像试衣镜
CN105184584A (zh) * 2015-09-17 2015-12-23 北京京东方多媒体科技有限公司 虚拟试衣系统及方法
CN105788002A (zh) * 2016-01-06 2016-07-20 湖南拓视觉信息技术有限公司 三维虚拟试鞋方法和系统
CN106022860A (zh) * 2016-05-06 2016-10-12 邓韬 一种匹配方法及装置
CN105956912A (zh) * 2016-06-06 2016-09-21 施桂萍 一种网络试衣的实现方法
CN106408364A (zh) * 2016-08-24 2017-02-15 刘陈 试衣方法及试衣系统
CN106339920A (zh) * 2016-08-24 2017-01-18 刘陈 试衣系统
CN106339929A (zh) * 2016-08-31 2017-01-18 潘剑锋 一种3d试衣系统
CN106933976B (zh) * 2017-02-14 2020-09-18 深圳奥比中光科技有限公司 建立人体3d净模型的方法及其在3d试衣中的应用
CN106954031A (zh) * 2017-02-20 2017-07-14 河南工程学院 一种智能一体化服装设计试穿控制系统
CN108961415A (zh) * 2017-05-24 2018-12-07 北京物语科技有限公司 基于深度图像采集设备的三维试衣方法及系统
CN107393011A (zh) * 2017-06-07 2017-11-24 武汉科技大学 一种基于多结构光视觉技术的快速三维虚拟试衣系统和方法
CN109146587A (zh) * 2017-06-16 2019-01-04 阿里巴巴集团控股有限公司 信息测量方法及装置
CN107862712A (zh) * 2017-10-20 2018-03-30 陈宸 尺寸数据确定方法、装置、存储介质及处理器
CN108009577A (zh) * 2017-11-29 2018-05-08 南京工业大学 一种虚拟试衣镜的实现方法
CN108171569B (zh) * 2017-12-11 2021-12-21 武汉纺织大学 一种反馈式智能服装推荐方法和系统
CN107958232A (zh) * 2017-12-26 2018-04-24 石狮市森科智能科技有限公司 基于体感交互的虚拟试衣方法、系统和试衣间
CN107993599A (zh) * 2017-12-29 2018-05-04 黄睿 一种服装推荐方法及广告机
CN107918909A (zh) * 2017-12-29 2018-04-17 南京信息职业技术学院 一种实体店虚拟试衣方法
CN108492163A (zh) * 2018-03-21 2018-09-04 江苏科技大学 一种基于数据集成处理的零售方法
CN110298720A (zh) * 2018-03-23 2019-10-01 真玫智能科技(深圳)有限公司 一种服装定制设计方法及平台
CN108564612A (zh) * 2018-03-26 2018-09-21 广东欧珀移动通信有限公司 模型显示方法、装置、存储介质及电子设备
CN108711091A (zh) * 2018-05-17 2018-10-26 张士鹏 一种基于ar技术的试衣购物系统以及方法
CN108648061A (zh) * 2018-05-18 2018-10-12 北京京东尚科信息技术有限公司 图像生成方法和装置
CN109003168A (zh) * 2018-08-16 2018-12-14 深圳Tcl数字技术有限公司 虚拟试衣方法、智能电视以及计算机可读存储介质
CN109461049A (zh) * 2018-10-19 2019-03-12 刘景江 一种利用虚拟现实技术的试衣方法及装置
CN111147842B (zh) * 2018-11-05 2023-05-02 北京京东尚科信息技术有限公司 基于可穿戴对象的匹配度确定方法、装置及设备
CN111324274A (zh) * 2018-12-13 2020-06-23 北京京东尚科信息技术有限公司 虚拟试妆方法、装置、设备及存储介质
CN109685911B (zh) * 2018-12-13 2023-10-24 谷东科技有限公司 一种可实现虚拟试衣的ar眼镜及其实现方法
CN109741390A (zh) * 2018-12-18 2019-05-10 维沃移动通信有限公司 一种尺码推荐方法及移动终端
CN109829794A (zh) * 2019-02-28 2019-05-31 深圳市翰香文化科技传媒有限公司 一种基于移动终端的虚拟试衣方法及虚拟试衣系统
CN110310167A (zh) * 2019-05-14 2019-10-08 洪岩 基于三维扫描和深度学习的个性化服装尺码匹配方法
CN110490708A (zh) * 2019-08-13 2019-11-22 东莞市纮萦服饰有限公司 一种虚拟试衣的方法
CN111080800A (zh) * 2019-12-18 2020-04-28 郭艺斌 一种基于人机交互的虚拟穿戴方法及虚拟穿戴系统
CN111179417B (zh) * 2019-12-31 2023-11-24 武汉科技大学 一种虚拟试穿、试戴系统及电子设备
CN111429213A (zh) * 2020-03-11 2020-07-17 青岛海尔智能技术研发有限公司 用于衣物模拟试穿的方法及装置、设备
CN111881351A (zh) * 2020-07-27 2020-11-03 深圳市爱深盈通信息技术有限公司 智能服饰推荐方法、装置、设备及存储介质
CN113012303B (zh) * 2021-03-10 2022-04-08 浙江大学 一种可保持服装纹理特征的多种类变尺度虚拟试衣方法
CN116188729A (zh) * 2021-11-25 2023-05-30 青岛海尔洗衣机有限公司 衣物处理设备的试衣方法及衣物处理设备

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102156810A (zh) * 2011-03-30 2011-08-17 北京触角科技有限公司 增强现实实时虚拟试衣系统及方法
US20120086783A1 (en) * 2010-06-08 2012-04-12 Raj Sareen System and method for body scanning and avatar creation
CN102842089A (zh) * 2012-07-18 2012-12-26 上海交通大学 基于3d真实人体模型及服装模型的网络虚拟试衣系统
CN102956004A (zh) * 2011-08-25 2013-03-06 鸿富锦精密工业(深圳)有限公司 虚拟试衣系统及方法
KR20130026380A (ko) * 2011-09-05 2013-03-13 삼성전자주식회사 이미지 기반의 가상 드레싱 시스템 및 방법
CN103106604A (zh) * 2013-01-23 2013-05-15 东华大学 基于体感技术的3d虚拟试衣方法

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20120086783A1 (en) * 2010-06-08 2012-04-12 Raj Sareen System and method for body scanning and avatar creation
CN102156810A (zh) * 2011-03-30 2011-08-17 北京触角科技有限公司 增强现实实时虚拟试衣系统及方法
CN102956004A (zh) * 2011-08-25 2013-03-06 鸿富锦精密工业(深圳)有限公司 虚拟试衣系统及方法
KR20130026380A (ko) * 2011-09-05 2013-03-13 삼성전자주식회사 이미지 기반의 가상 드레싱 시스템 및 방법
CN102842089A (zh) * 2012-07-18 2012-12-26 上海交通大学 基于3d真实人体模型及服装模型的网络虚拟试衣系统
CN103106604A (zh) * 2013-01-23 2013-05-15 东华大学 基于体感技术的3d虚拟试衣方法

Cited By (58)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP3569244A1 (en) 2015-09-23 2019-11-20 CytoImmune Therapeutics, LLC Flt3 directed car cells for immunotherapy
WO2017069958A2 (en) 2015-10-09 2017-04-27 The Brigham And Women's Hospital, Inc. Modulation of novel immune checkpoint targets
US11180730B2 (en) 2015-10-28 2021-11-23 The Broad Institute, Inc. Compositions and methods for evaluating and modulating immune responses by detecting and targeting GATA3
US11186825B2 (en) 2015-10-28 2021-11-30 The Broad Institute, Inc. Compositions and methods for evaluating and modulating immune responses by detecting and targeting POU2AF1
US11884717B2 (en) 2015-11-19 2024-01-30 The Brigham And Women's Hospital, Inc. Method of treating autoimmune disease with lymphocyte antigen CD5-like (CD5L) protein
WO2017087708A1 (en) 2015-11-19 2017-05-26 The Brigham And Women's Hospital, Inc. Lymphocyte antigen cd5-like (cd5l)-interleukin 12b (p40) heterodimers in immunity
US11001622B2 (en) 2015-11-19 2021-05-11 The Brigham And Women's Hospital, Inc. Method of treating autoimmune disease with lymphocyte antigen CD5-like (CD5L) protein
WO2018049025A2 (en) 2016-09-07 2018-03-15 The Broad Institute Inc. Compositions and methods for evaluating and modulating immune responses
WO2018067991A1 (en) 2016-10-07 2018-04-12 The Brigham And Women's Hospital, Inc. Modulation of novel immune checkpoint targets
US12447213B2 (en) 2016-10-07 2025-10-21 The Broad Institute, Inc. Modulation of novel immune checkpoint targets
US12227578B2 (en) 2016-11-11 2025-02-18 The Broad Institute, Inc. Modulation of intestinal epithelial cell differentiation, maintenance and/or function through T cell action
US11963966B2 (en) 2017-03-31 2024-04-23 Dana-Farber Cancer Institute, Inc. Compositions and methods for treating ovarian tumors
US11913075B2 (en) 2017-04-01 2024-02-27 The Broad Institute, Inc. Methods and compositions for detecting and modulating an immunotherapy resistance gene signature in cancer
US12590288B2 (en) 2017-04-12 2026-03-31 The Broad Institute, Inc. Method of treating an inflammatory disease by administering an agent which binds a surface receptor on a tuft cell that induces an ILC class 2 inflammatory response
WO2018191553A1 (en) 2017-04-12 2018-10-18 Massachusetts Eye And Ear Infirmary Tumor signature for metastasis, compositions of matter methods of use thereof
US12226479B2 (en) 2017-05-11 2025-02-18 The General Hospital Corporation Methods and compositions of use of CD8+ tumor infiltrating lymphocyte subtypes and gene signatures thereof
US11897953B2 (en) 2017-06-14 2024-02-13 The Broad Institute, Inc. Compositions and methods targeting complement component 3 for inhibiting tumor growth
US12049643B2 (en) 2017-07-14 2024-07-30 The Broad Institute, Inc. Methods and compositions for modulating cytotoxic lymphocyte activity
US12043870B2 (en) 2017-10-02 2024-07-23 The Broad Institute, Inc. Methods and compositions for detecting and modulating an immunotherapy resistance gene signature in cancer
WO2019070755A1 (en) 2017-10-02 2019-04-11 The Broad Institute, Inc. METHODS AND COMPOSITIONS FOR DETECTING AND MODULATING A GENETIC SIGNATURE OF IMMUNOTHERAPY RESISTANCE IN CANCER
US11732257B2 (en) 2017-10-23 2023-08-22 Massachusetts Institute Of Technology Single cell sequencing libraries of genomic transcript regions of interest in proximity to barcodes, and genotyping of said libraries
US12171783B2 (en) 2017-11-13 2024-12-24 The Broad Institute, Inc. Methods and compositions for targeting developmental and oncogenic programs in H3K27M gliomas
WO2019094983A1 (en) 2017-11-13 2019-05-16 The Broad Institute, Inc. Methods and compositions for treating cancer by targeting the clec2d-klrb1 pathway
US11994512B2 (en) 2018-01-04 2024-05-28 Massachusetts Institute Of Technology Single-cell genomic methods to generate ex vivo cell systems that recapitulate in vivo biology with improved fidelity
EP4495246A2 (en) 2018-03-01 2025-01-22 University of Kansas Techniques for generating cell-based therapeutics using recombinant t cell receptor genes
US11957695B2 (en) 2018-04-26 2024-04-16 The Broad Institute, Inc. Methods and compositions targeting glucocorticoid signaling for modulating immune responses
WO2019232542A2 (en) 2018-06-01 2019-12-05 Massachusetts Institute Of Technology Methods and compositions for detecting and modulating microenvironment gene signatures from the csf of metastasis patients
US12036240B2 (en) 2018-06-14 2024-07-16 The Broad Institute, Inc. Compositions and methods targeting complement component 3 for inhibiting tumor growth
WO2020072700A1 (en) 2018-10-02 2020-04-09 Dana-Farber Cancer Institute, Inc. Hla single allele lines
WO2020081730A2 (en) 2018-10-16 2020-04-23 Massachusetts Institute Of Technology Methods and compositions for modulating microenvironment
EP3867855A4 (en) * 2018-10-19 2021-12-15 Perfitly, LLC. PERFITLY AR / VR PLATFORM
WO2020131586A2 (en) 2018-12-17 2020-06-25 The Broad Institute, Inc. Methods for identifying neoantigens
US11739156B2 (en) 2019-01-06 2023-08-29 The Broad Institute, Inc. Massachusetts Institute of Technology Methods and compositions for overcoming immunosuppression
WO2020186101A1 (en) 2019-03-12 2020-09-17 The Broad Institute, Inc. Detection means, compositions and methods for modulating synovial sarcoma cells
WO2020191079A1 (en) 2019-03-18 2020-09-24 The Broad Institute, Inc. Compositions and methods for modulating metabolic regulators of t cell pathogenicity
WO2020236967A1 (en) 2019-05-20 2020-11-26 The Broad Institute, Inc. Random crispr-cas deletion mutant
WO2020243371A1 (en) 2019-05-28 2020-12-03 Massachusetts Institute Of Technology Methods and compositions for modulating immune responses
WO2021030627A1 (en) 2019-08-13 2021-02-18 The General Hospital Corporation Methods for predicting outcomes of checkpoint inhibition and treatment thereof
US12421557B2 (en) 2019-08-16 2025-09-23 The Broad Institute, Inc. Methods for predicting outcomes and treating colorectal cancer using a cell atlas
WO2021041922A1 (en) 2019-08-30 2021-03-04 The Broad Institute, Inc. Crispr-associated mu transposase systems
US12297426B2 (en) 2019-10-01 2025-05-13 The Broad Institute, Inc. DNA damage response signature guided rational design of CRISPR-based systems and therapies
US12394502B2 (en) 2019-10-02 2025-08-19 The General Hospital Corporation Method for predicting HLA-binding peptides using protein structural features
US11981922B2 (en) 2019-10-03 2024-05-14 Dana-Farber Cancer Institute, Inc. Methods and compositions for the modulation of cell interactions and signaling in the tumor microenvironment
US12195725B2 (en) 2019-10-03 2025-01-14 Dana-Farber Cancer Institute, Inc. Compositions and methods for modulating and detecting tissue specific TH17 cell pathogenicity
US11793787B2 (en) 2019-10-07 2023-10-24 The Broad Institute, Inc. Methods and compositions for enhancing anti-tumor immunity by targeting steroidogenesis
US11844800B2 (en) 2019-10-30 2023-12-19 Massachusetts Institute Of Technology Methods and compositions for predicting and preventing relapse of acute lymphoblastic leukemia
US12165747B2 (en) 2020-01-23 2024-12-10 The Broad Institute, Inc. Molecular spatial mapping of metastatic tumor microenvironment
WO2021212069A1 (en) 2020-04-17 2021-10-21 City Of Hope Flt3-targeted chimeric antigen receptor modified cells for treatment of flt3-positive malignancies
US12271969B2 (en) 2020-05-15 2025-04-08 3M Innovative Properties Company Personal protective equipment training system with user-specific augmented reality content construction and rendering
CN112884638A (zh) * 2021-02-02 2021-06-01 北京东方国信科技股份有限公司 虚拟试衣方法及装置
CN114663199A (zh) * 2022-05-17 2022-06-24 武汉纺织大学 一种动态展示的实时三维虚拟试衣系统及方法
CN114663199B (zh) * 2022-05-17 2022-08-30 武汉纺织大学 一种动态展示的实时三维虚拟试衣系统及方法
WO2024077256A1 (en) 2022-10-07 2024-04-11 The General Hospital Corporation Methods and compositions for high-throughput discovery ofpeptide-mhc targeting binding proteins
CN115661354A (zh) * 2022-11-07 2023-01-31 深圳市十二篮服饰有限公司 一种3d智能试衣模型系统
WO2024124044A1 (en) 2022-12-07 2024-06-13 The Brigham And Women’S Hospital, Inc. Compositions and methods targeting sat1 for enhancing anti¬ tumor immunity during tumor progression
WO2025059533A1 (en) 2023-09-13 2025-03-20 The Broad Institute, Inc. Crispr enzymes and systems
WO2025097055A2 (en) 2023-11-02 2025-05-08 The Broad Institute, Inc. Compositions and methods of use of t cells in immunotherapy
WO2025117544A1 (en) 2023-11-29 2025-06-05 The Broad Institute, Inc. Engineered omega guide molecule and iscb compositions, systems, and methods of use thereof

Also Published As

Publication number Publication date
CN104091269A (zh) 2014-10-08

Similar Documents

Publication Publication Date Title
WO2016000304A1 (zh) 一种虚拟试衣方法及虚拟试衣系统
US12450804B2 (en) Processing user selectable product images and facilitating visualization-assisted virtual dressing
EP3479296B1 (en) System of virtual dressing utilizing image processing, machine learning, and computer vision
US20150134302A1 (en) 3-dimensional digital garment creation from planar garment photographs
KR101707707B1 (ko) 인체 모델을 이용한 가상 아이템 피팅 방법 및 가상 아이템의 피팅 서비스 제공 시스템
US8976230B1 (en) User interface and methods to adapt images for approximating torso dimensions to simulate the appearance of various states of dress
US11620762B2 (en) Systems and methods for sizing objects via a computing device
JP5439787B2 (ja) カメラ装置
CN106256122A (zh) 图像处理设备和图像处理方法
CN108292449A (zh) 使用手势修改三维服装
TW201337815A (zh) 電子試衣方法和電子試衣裝置
TW201401222A (zh) 具有虛擬試衣功能的電子裝置及虛擬試衣方法
US9396555B2 (en) Reference based sizing
US20200074667A1 (en) Clothing Size Determination Systems and Methods of Use
CN107481082A (zh) 一种虚拟试衣方法及其装置、电子设备及虚拟试衣系统
US20150269759A1 (en) Image processing apparatus, image processing system, and image processing method
CN106127552A (zh) 一种虚拟场景显示方法、装置及系统
CN102254094A (zh) 服装试穿系统及服装试穿方法
CN112997218B (zh) 用于估计服装的尺码的方法和系统
JP2015509193A (ja) 身体部分の測定
US8803914B2 (en) Machine-implemented method, system and computer program product for enabling a user to virtually try on a selected garment using augmented reality
CN107430542A (zh) 获取图像和制作服装的方法
KR20200015236A (ko) 단말기 상에서 체형 정보를 입력하는 방법 및 입력된 체형 정보에 기초하여 맞춤 의류를 추천하는 방법과 시스템
JP2017110308A (ja) 最適ブラジャー選定装置および最適ブラジャー選定プログラム
TWI637353B (zh) 測量裝置及測量方法

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 14896391

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

32PN Ep: public notification in the ep bulletin as address of the adressee cannot be established

Free format text: NOTING OF LOSS OF RIGHTS PURSUANT TO RULE 112(1) EPC (EPO FORM 1205A DATED 12/05/17)

122 Ep: pct application non-entry in european phase

Ref document number: 14896391

Country of ref document: EP

Kind code of ref document: A1