Generating of 3d-printed custom wearables

Abstract

Disclosed is a platform for generating and delivering 3-D printed wearables. The platform includes scanning, image processing, machine learning, computer vision, and user input to generate a printed wearable. Scanning occurs in a number of ways across a number of devices. The variability of scanning generates a number of scanning output types. Outputs from the scanning process are normalized into a single type during image processing. The computer vision and machine learning portions of the platform use the normalized body scan to develop models that may be used by a 3D printer to generate a wearable customized to the user. The platform further provides opportunities for the user to check the work of the scanning, image processing, computer vision, and machine learning. The user input enables the platform to improve and inform the machine learning aspects.

1 . A method comprising:
 receiving, through an application program interface (API), body part image data of a part of a living body;   determining a set of physical dimensions of the body part by using a plurality of images of the body part image data as parallax viewpoints, wherein a position of each parallax viewpoint and a set of points on the part of the living body identified via pixel recognition are used to identify a depth, and wherein the depth is used to derive the set of physical dimensions;   generating a digital model of the body part based on the set of physical dimensions;   generating a 3D model of a wearable corresponding to the body part based on the digital model; and   sending print instructions to a 3D printer including information associated with printing the 3D model of the wearable to a physical wearable.   
     
     
         2 . The method of  claim 1 , further comprising:
 receiving a message, by the API, from a user, the message accepting the 3D model of the wearable; and   printing, by a 3D printer, a wearable corresponding to the 3D model of the wearable.   
     
     
         3 . The method of  claim 1 , further comprising:
 receiving, by a mobile device application, part images of the living body from a mobile device camera;   filtering, by the mobile device application, the body part images into accepted images and rejected images based upon a computer vision comparison to a set of expected images; and   communicating, by the mobile device application, accepted images to the API as the body part image data.   
     
     
         4 . The method of  claim 1 , further comprising:
 receiving, by a mobile device application, images of the living body from a mobile device camera, the images including a predetermined reference object having known dimensions; and   wherein determining the set of physical dimensions further includes a comparison of the body part to the reference object.   
     
     
         5 . The method of  claim 1 , wherein the part of the living body is a foot, and the 3D model of a wearable is a footwear insert. 
     
     
         6 . The method of  claim 5 , further comprising:
 receiving, by a mobile device application, foot images of the living body from a mobile device camera, the foot images including a predetermined reference object having known dimensions; and   wherein determining the set of physical dimensions further includes a comparison of the body part to the reference object.   
     
     
         7 . The method of  claim 6 , wherein the reference object is a sheet of standardized sized paper. 
     
     
         8 . The method of  claim 3 , further comprising:
 issuing instructions, by the mobile device application, to a user of an associated mobile device depicting expected positioning of the body part.   
     
     
         9 . The method of  claim 1 , wherein the body part image data comprises at least one of:
 infrared imaging data;   confocal microscopy data;   lightfield imaging data; or   ultrasound imaging data.   
     
     
         10 . The method of  claim 1 , further comprising:
 collecting, by a mobile application of a mobile device, video data of a part of a living body, the video data including a video clip wherein a film perspective rotates about the part of the living body; and   extracting image frames from the video data, the image frames including the part of the living body captured at a number of perspectives, wherein the image frames are determined by comparing and matching each frame of the video data to reference frames, wherein the reference frames preexist the video data.   
     
     
         11 . The method of  claim 1 , further comprising:
 printing, by a 3D printer, a wearable corresponding to the 3D model of the wearable;   generating a time-lapse video depicting said printing step; and   transmitting the time-lapse video to a web host for hosting.   
     
     
         12 . The method of  claim 1 , wherein the received body image data is of a first format, the first format is computer readable and one of a number of predetermined formats, and wherein the generating a digital model of the body part step further comprises:
 identifying the first format from the number of predetermined formats;   determining a subset of data to extract from the body image data of the first format to use in converting at least a portion of the body image data to a result format;   extracting the subset of the body image data from the body image data; and   converting the subset of the body image data to the result format.   
     
     
         13 . A system comprising:
 a network-connected server configured to process body part image data of a part of a living body, and to generate a 3D model of a wearable corresponding to the body part based on the body part image data, wherein a set of physical dimensions of the body part is calculated using a plurality of images of the body part image data as parallax viewpoints, wherein a position of each parallax viewpoint and a set of points on the part of the living body identified via pixel recognition are used to identify a depth, and wherein the depth is used to derive the set of physical dimensions; and   an API instantiated on a number of devices external to the server and configured to communicate with the server, the API configured to receive the body part image data on a first device of the external devices and to expose the corresponding 3D model of the wearable to at least a subset of the number of external devices.   
     
     
         14 . The system of  claim 13 , further comprising:
 a communication interface configured to output the 3D model of the wearable to a 3D printer to print the wearable from the 3D model of the wearable.   
     
     
         15 . The system of  claim 13 , further comprising:
 a mobile device application instanced on a mobile device, the mobile device application in communication with the web server via a mobile device network communicator and is integrated with the API, the mobile device application configured to interface with a mobile device camera and capture body part image data.   
     
     
         16 . The system of  claim 14 , further comprising:
 a video server that hosts time-lapse videos that are accessible from the Internet.   
     
     
         17 . A method comprising:
 receiving, through an application program interface (API), body part image data of a part of a living body;   determining a set of physical dimensions of the body part without use of a reference object in the body part image data, wherein the body part image data is derived from a single-lens visible light photodetector;   generating a digital model of the body part based on the set of physical dimensions;   generating a 3D model of a wearable corresponding to the body part based on the digital model; and   sending print instructions to a 3D printer including information associated with printing the 3D model of the wearable to a physical wearable.   
     
     
         18 . The method of  claim 17 , further comprising:
 receiving, by a mobile device application, part images of the living body from a mobile device camera;   filtering, by the mobile device application, the body part images into accepted images and rejected images based upon a computer vision comparison to a set of expected images; and   communicating, by the mobile device application, accepted images to the API as the body part image data.   
     
     
         19 . The method of  claim 18 , further comprising:
 issuing instructions, by the mobile device application, to a user of an associated mobile device depicting expected positioning of the body part.   
     
     
         20 . The method of  claim 17 , further comprising:
 collecting, by a mobile application of a mobile device, video data of a part of a living body, the video data including a video clip wherein a film perspective rotates about the part of the living body; and   extracting image frames from the video data, the image frames including the part of the living body captured at a number of perspectives, wherein the image frames are determined by comparing and matching each frame of the video data to reference frames, wherein the reference frames preexist the video data.