Method and system to create custom, user-specific eyewear

• US 10,459,256 B2
• Filed: 02/10/2015
• Issued: 10/29/2019
• Est. Priority Date: 08/22/2013
• Status: Active Grant

• Current Assignee: Bespoke Inc.
• Original Assignee: Bespoke Inc.
• Inventors: Fonte, Timothy A., Varady, Eric J.
• Primary Examiner(s): Wilkes, Zachary W
• Application Number:
  US14/618,765
• Publication Number:
  US 20150154679A1
• Time in Patent Office: 1,722 Days
• Field of Search: 351178
• CPC Class Codes: A61B 3/0041 characterised by display arrangements
• CPC Class Codes: A61B 3/111 for measuring interpupillary distance
• CPC Class Codes: B29D 12/02 Spectacle frames constructional form G02C
• CPC Class Codes: B33Y 10/00 Processes of additive manufacturing
• CPC Class Codes: B33Y 50/00 Data acquisition or data processing for additive manufacturing
• CPC Class Codes: B33Y 80/00 Products made by additive manufacturing
• CPC Class Codes: G02C 13/001 Assembling; Repairing
• CPC Class Codes: G02C 13/003 Measuring during assembly or fitting of spectacles
• CPC Class Codes: G02C 13/005 Measuring geometric parameters required to locate ophtalmic lenses in spectacles frames apparatus for testing or instruments for examining the eyes per se A61B3/00; machines or devices and accessories for grinding the edges of lenses using spectacles as a template B24B9/144
• CPC Class Codes: G02C 7/024 Methods of designing ophthalmic lenses
• CPC Class Codes: G02C 7/027 considering wearer's parameters
• CPC Class Codes: G06F 16/22 Indexing; Data structures therefor; Storage structures
• CPC Class Codes: G06F 30/00 Computer-aided design [CAD]
• CPC Class Codes: G06Q 30/0621 Item configuration or customization
• CPC Class Codes: G06T 19/20 Editing of 3D images, e.g. changing shapes or colours, aligning objects or positioning parts
• CPC Class Codes: G06T 2219/2012 Colour editing, changing, or manipulating; Use of colour codes
• CPC Class Codes: G06V 40/166 using acquisition arrangements
• CPC Class Codes: G06V 40/169 Holistic features and representations, i.e. based on the facial image taken as a whole
• CPC Class Codes: G16B 5/00 ICT specially adapted for modelling or simulations in systems biology, e.g. gene-regulatory networks, protein interaction networks or metabolic networks
• CPC Class Codes: G16H 50/50 for simulation or modelling of medical disorders
• CPC Class Codes: H04L 65/403 : Arrangements for multi-party communication, e.g. for conferences data switching systems for conference H04L12/18; arrangements for connecting several subscribers to a common circuit, i.e. affording conference facilities H04M3/56; television conferencing systems H04N7/15
• CPC Class Codes: H04N 23/611 : where the recognised objects include parts of the human body

Abstract

Systems and methods for creating fully custom products from scratch without exclusive use of off-the-shelf or pre-specified components. A system for creating custom products includes a computer communicatively coupled with an image capture device and configured to construct an anatomic model of the user based on captured image data and/or measurement data. The computer provides a configurable product model and enables preview and automatic or user guided customization of the product model. A display is communicatively coupled with the computer and displays the custom product model superimposed on the anatomic model or image data of the user. The computer is further configured to provide the customized product model to a manufacturer for manufacturing eyewear for the user in accordance with the customized product model.

Claims

1. A computer-implemented method for creating a model of an individual-specific eyewear product, using a computer system, the method comprising:

receiving, over an electronic network, and classifying one or more facial feature characteristics of users in a population of users;

storing an association between the classified one or more facial feature characteristics and at least one eyewear design attribute;

receiving, over an electronic network, or computing an individual-specific characteristic from image data of an individual outside of the population of users;

predicting an individual-specific eyewear design attribute for the individual based on the individual-specific characteristic and the stored association;

determining a first model of an eyewear product selected for the individual based on the predicted individual-specific eyewear design attribute, the first model comprising a solid model or a surface model of the eyewear product;

determining one or more configurable features of a geometry of a frame of the first model of the eyewear product;

quantifying at least a surface or a contour of an anatomic feature of the individual based on the image data of the individual;

generating a second model of the eyewear product by shaping a surface or a contour of the first model of the eyewear product to match the quantified surface or quantified contour of the anatomic feature of the individual while maintaining one or more parametric constraints on the geometry of the second model, the second model comprising a solid model or a surface model of the eyewear product; and

generating instructions for manufacturing the individual-specific eyewear product based on the second model.

2. The method of claim 1, wherein the individual-specific eyewear design attribute includes:

an eyewear fit, geometry, size, suggested style, aesthetic, material, shape, color, finish, width, thickness, position on the individual'"'"'s face, and/or lens size;

or

wherein the individual-specific eyewear design attribute or the received individual-specific characteristic are determined automatically.

3. The method of claim 1, wherein the individual-specific characteristic includes characterizations of one or more anatomical parameters, preferences, aesthetic characteristics, demographics, and/or activities associated with the individual.

4. The method of claim 3, wherein the one or more preferences associated with the individual include the individual'"'"'s style descriptors, attire, eyewear style, eyewear material, eyewear shape, color, eyewear finish, eyewear position on the individual'"'"'s face, and/or eyewear lens size;

wherein the one or more aesthetic characteristics associated with the individual include the individual'"'"'s skin features, facial features, and/or hair features;

wherein the one or more demographics associated with the individual include the individual'"'"'s age, gender, ethnicity, local trends, and/or occupation; and

wherein the one or more activities associated with the individual include the individual'"'"'s word usage, places visited, and/or artistic preferences.

5. The method of claim 4, further comprising:

appending a weight, or enabling the individual to append a weight, to the individual-specific characteristic, the weight representing a significance of the individual-specific characteristic to an algorithm for predicting the individual-specific eyewear design attribute.

6. The method of claim 1, further comprising:

generating an electronic representation of the second model in spatial relation to image information representing the individual.

7. The method of claim 6, wherein the electronic representation of the second model includes an interactive user interface having one or more user elements configured to receive input from the individual, the input including the individual-specific characteristic and/or the modification to the one or more configurable features of the second model.

8. The method of claim 7, further comprising:

generating the one or more user elements to receive input from the individual based on previously received input from the individual or input from one or more users.

9. The method of claim 1, further comprising:

predicting the individual-specific eyewear design attribute based on data generated by expert designers or test users.

10. The method of claim 1, further comprising:

predicting the individual-specific eyewear design attribute using a machine learning algorithm.

11. The method of claim 10, further comprising:

updating the machine learning algorithm or training the machine learning algorithm, in real-time, based on real-time preferences received from the individual and/or users.

12. The method of claim 10, further comprising:

training the machine learning algorithm to associate eyewear design attributes and population-based user characteristics based on analyses of user images using one or more image-based characteristics or one or more image filtering techniques.

13. The method of claim 12, further comprising:

classifying the individual into one or more groups, or the individual as having one or more demographics, based on one or more of the analyses; and

predicting the individual-specific eyewear design attribute based on the classifying.

14. The method of claim 1, further comprising:

generating a look-up table to compare the individual-specific characteristic to the population-based anatomical user characteristic in order to predict the individual-specific eyewear design attribute.

15. The method of claim 1, further comprising:

ranking one or more eyewear design attributes based on predictions made from the individual-specific characteristic.

16. The method of claim 1, further including:

importing the individual-specific characteristic from a social network, user profile, and/or advertising database information.

17. The method of claim 1,

machining instructions or files, a command for producing or ordering production of one or more portions of the individual-specific eyewear product, one or more prompts for machining, inspection, or quality control of the individual-specific eyewear product, or a combination thereof.

18. The method of claim 1, wherein a modification to one of the one or more configurable features is received from the individual'"'"'s input of one or more fit preferences, or from one or more fit preferences inferred or extracted from one or more images of the individual.

19. A system for creating a model of an individual-specific eyewear product, the system comprising:

a data storage device storing instructions for creating the model of the individual-specific eyewear product; and

a processor configured to execute the instructions to perform a method comprising;

receiving, over an electronic network, and classifying one or more facial feature characteristics of users in a population of users;

storing an association between the classified one or more facial feature characteristics and at least one eyewear design attribute;

receiving, over an electronic network, or computing an individual-specific characteristic from image data of an individual outside of the population of users;

predicting an individual-specific eyewear design attribute for the individual based on the individual-specific characteristic and the stored association;

determining a first model of an eyewear product selected for the individual based on the predicted individual-specific eyewear design attribute, the first model comprising a solid model or a surface model of the eyewear product;

determining one or more configurable features of a geometry of a frame of the first model of the eyewear product;

quantifying at least a surface or a contour of an anatomic feature of the individual based on the image data of the individual;

generating a second model of the eyewear product by shaping a surface or a contour of the first model of the eyewear product to match the quantified surface or quantified contour of the anatomic feature of the individual while maintaining one or more parametric constraints on the geometry of the second model, the second model comprising a solid model or a surface model of the eyewear product;

and

generating instructions for manufacturing the individual-specific eyewear product based on the second model.

20. A non-transitory computer readable medium for use on a computer system containing computer-executable programming instructions for performing a method of creating a model of an individual-specific eyewear product, the method comprising:

receiving, over an electronic network, and classifying one or more facial feature characteristics of users in a population of users;

storing an association between the classified one or more facial feature characteristics and at least one eyewear design attribute;

receiving, over an electronic network, or computing an individual-specific characteristic from image data of an individual outside of the population of users;

predicting an individual-specific eyewear design attribute for the individual based on the individual-specific characteristic and the stored association;

determining a first model of an eyewear product selected for the individual based on the predicted individual-specific eyewear design attribute, the first model comprising a solid model or a surface model of the eyewear product;

determining one or more configurable features of a geometry of a frame of the first model of the eyewear product;

quantifying at least a surface or a contour of an anatomic feature of the individual based on the image data of the individual;

generating a second model of the eyewear product by shaping a surface or a contour of the first model of the eyewear product to match the quantified surface or quantified contour of the anatomic feature of the individual while maintaining one or more parametric constraints on the geometry of the second model, the second model comprising a solid model or a surface model of the eyewear product;

and

generating instructions for manufacturing the individual-specific eyewear product based on the second model.