Patent Publication Number: US-2015062116-A1

Title: Systems and methods for rapidly generating a 3-d model of a user

Description:
BACKGROUND 
     The use of computer systems and computer-related technologies continues to increase at a rapid pace. This increased use of computer systems has influenced the advances made to computer-related technologies. Indeed, computer systems have increasingly become an integral part of the business world and the activities of individual consumers. Computers have opened up an entire industry of internet shopping. In many ways, online shopping has changed the way consumers purchase products. For example, a consumer may want to know what they will look like in and/or with a product. On the webpage of a certain product, a photograph of a model with the particular product may be shown. However, users may want to see more accurate depictions of themselves in relation to various products. 
     SUMMARY 
     According to at least one embodiment, a computer-implemented method for generating a three-dimensional (3-D) model of a user is described. A plurality of images of a user may be captured. A 3-D model of the user may be generated using the captured plurality of images of the user and 3-D data derived from processing a previously captured plurality of images of the user. 
     In one embodiment, a feature of the user may be tracked in real time based at least in part on the 3-D data derived from processing the previously captured plurality of images. The previously captured plurality of images may be captured. The previously captured plurality of images may be processed prior to capturing the plurality of images. In one embodiment, scaling data may be derived from a scaling image of the user to scale the 3-D data. The scaling image of the user may be captured in conjunction with the capturing of the previously captured plurality of images. 
     The 3-D model of the user may be generated using the scaling data derived from the scaling image of the user. Prior to capturing the plurality of images of the user, a 3-D modeling process may be performed on the previously captured plurality of images and the scaling image. Results of processing the previously captured plurality of images may be received. The results of processing the previously captured plurality of images may include the 3-D data. Results of processing the scaling image may be received. The results of processing the scaling image may include the scaling data. Prior to capturing the plurality of images of the user, a previous 3-D model of the user may be generated using the 3-D data derived from processing the previously captured plurality of images. The previous 3-D model of the user may be scaled using the scaling data derived from a scaling image of the user. 
     A computing device configured to generate a three-dimensional (3-D) model of a user is also described. The device may include a processor and memory in electronic communication with the processor. The memory may store instructions that are executable by the processor to capture a plurality of images of a user and to generate a 3-D model of the user using the captured plurality of images of the user and 3-D data derived from processing a previously captured plurality of images of the user. 
     A computer-program product to generate a three-dimensional (3-D) model of a user is also described. The computer-program product may include a non-transitory computer-readable medium that stores instructions. The instructions may be executable by a processor to capture a plurality of images of a user and to generate a 3-D model of the user using the captured plurality of images of the user and 3-D data derived from processing a previously captured plurality of images of the user. 
     Features from any of the above-mentioned embodiments may be used in combination with one another in accordance with the general principles described herein. These and other embodiments, features, and advantages will be more fully understood upon reading the following detailed description in conjunction with the accompanying drawings and claims. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The accompanying drawings illustrate a number of exemplary embodiments and are a part of the specification. Together with the following description, these drawings demonstrate and explain various principles of the instant disclosure. 
         FIG. 1  is a block diagram illustrating one embodiment of an environment in which the present systems and methods may be implemented; 
         FIG. 2  is a block diagram illustrating another embodiment of an environment in which the present systems and methods may be implemented; 
         FIG. 3  is a block diagram illustrating one example of a model generator; 
         FIG. 4  illustrates an example arrangement for capturing an image of a user; 
         FIG. 5  is a diagram illustrating an example of a device for capturing an image of a user; 
         FIG. 6  illustrates an example arrangement of a virtual 3-D space including a depiction of a 3-D model of a user; 
         FIG. 7  is a flow diagram illustrating one embodiment of a method for generating a 3-D model of a user; 
         FIG. 8  is a flow diagram illustrating one embodiment of a method for tracking a feature of the user in real-time; 
         FIG. 9  is a flow diagram illustrating one embodiment of a method for generating a 3-D model from previously captured images; and 
         FIG. 10  depicts a block diagram of a computer system suitable for implementing the present systems and methods. 
     
    
    
     While the embodiments described herein are susceptible to various modifications and alternative forms, specific embodiments have been shown by way of example in the drawings and will be described in detail herein. However, the exemplary embodiments described herein are not intended to be limited to the particular forms disclosed. Rather, the instant disclosure covers all modifications, equivalents, and alternatives falling within the scope of the appended claims. 
     DETAILED DESCRIPTION OF EXEMPLARY EMBODIMENTS 
     The systems and methods described herein relate to the virtually trying-on of products. Three-dimensional (3-D) computer graphics are graphics that use a 3-D representation of geometric data that is stored in the computer for the purposes of performing calculations and rendering two-dimensional (2-D) images. Such images may be stored for viewing later or displayed in real-time. A 3-D space may include a mathematical representation of a 3-D surface of an object. A 3-D model may be contained within a graphical data file. A 3-D model may represent a 3-D object using a collection of points in 3-D space, connected by various geometric entities such as triangles, lines, curved surfaces, etc. Being a collection of data (points and other information), 3-D models may be created by hand, algorithmically (procedural modeling), or scanned such as with a laser scanner. A 3-D model may be displayed visually as a two-dimensional image through a process called 3-D rendering, or used in non-graphical computer simulations and calculations. In some cases, the 3-D model may be physically created using a 3-D printing device. 
     A device may capture an image of a user and generate a 3-D model of the user from the image. A 3-D polygon mesh of an object may be placed in relation to the 3-D model of the user to create a 3-D virtual depiction of the user wearing the object (e.g., a pair of glasses, a hat, a shirt, a belt, etc.). This 3-D scene may then be rendered into a 2-D image to provide the user a virtual depiction of the user in relation to the object. Although some of the examples used herein describe articles of clothing, such as a virtual try-on pair of glasses, it is understood that the systems and methods described herein may be used to virtually try-on a wide variety of products. Examples of such products may include glasses, clothing, footwear, jewelry, accessories, hair styles, etc. 
       FIG. 1  is a block diagram illustrating one embodiment of an environment  100  in which the present systems and methods may be implemented. In some embodiments, the systems and methods described herein may be performed on a single device (e.g., device  102 ). For example, a model generator  104  may be located on device  102 . Examples of device  102  include mobile devices, smart phones, personal computing devices, computers, servers, etc. 
     In some configurations, device  102  may include model generator  104 , camera  106 , and display  108 . In one example, device  102  may be coupled to a database  110 . In one embodiment, database  110  may be internal to device  102 . In another embodiment, database  110  may be external to device  102 . In some configurations, database  110  may include 3-D data  112  and scaling data  114 . 
     In one embodiment, model generator  104  may enable a user to initiate a process to generate a 3-D model of the user. In some configurations, model generator  104  may obtain multiple images of the user. For example, model generator  104  may capture multiple images of a user via camera  106 . For instance, model generator  104  may capture a video (e.g., a 5 second video) via camera  106 . Alternatively, model generator  104  may capture one or more photographs via camera  106 . In some configurations, model generator  104  may use 3-D data  112  and scaling data  114  to generate a 3-D representation of a user. For example, 3-D data  112  may include vertex coordinates of a polygon model of a user (e.g., a user&#39;s head, face, hand, etc.). Thus, model generator  104  may generate a 3-D model of a user using 3-D data  112  and scaling data  114 . In some embodiments, 3-D data  112  may include a polygon model of an object. In some configurations, the scaling data  114  may define a visual aspect (e.g., pixel information) of the 3-D model of the object such as color, texture, shadow, or transparency. 
     In some configurations, model generator  104  may generate a first 3-D model of a user from a first plurality of images of the user. The first plurality of images may include at least one scaling image of the user. Model generator  104  may derive 3-D data by processing the first plurality of images. Model generator  104  may derive scaling data from the at least one scaling image of the user. A first 3-D model of the user may be generated, via model generator  104 , using the derived 3-D data and scaling data. Model generator  104  may capture a second plurality of images of the user after processing the first plurality of images (e.g., deriving 3-D data and scaling data from the first plurality of images). A second 3-D model of the user may be generated, via model generator  104 , using the second plurality of images and the 3-D data and scaling data derived from the first plurality of images. 
       FIG. 2  is a block diagram illustrating another embodiment of an environment  200  in which the present systems and methods may be implemented. In some embodiments, a device  102 - a  may communicate with a server  206  via a network  204 . Example of networks  204  include, local area networks (LAN), wide area networks (WAN), virtual private networks (VPN), wireless networks (using 802.11, for example), cellular networks (using 3G and/or LTE, for example), etc. In some configurations, the network  204  may include the internet. In some configurations, device  102 - a  may be one example of device  102  illustrated in  FIG. 1 . For example, device  102 - a  may include camera  106 , display  108 , and application  202 . It is noted that in some embodiments, device  102 - a  may not include model generator  104 . In some embodiments, both device  102 - a  and server  206  may include model generator  104  where at least a portion of the functions of model generator  104  are performed separately and/or concurrently on both device  102 - a  and server  206 . 
     In some embodiments, server  206  may include model generator  104  and may be coupled to the database  110 . For example, model generator  104  may access 3-D data  112  and scaling data  114  in database  110  via server  206 . The database  110  may be internal or external to server  206 . 
     In some configurations, the application  202  may capture multiple images via camera  106 . For example, the application  202  may use camera  106  to capture a video. Upon capturing the multiple images, the application  202  may process the multiple images to generate 3-D data and/or scaling data. In some embodiments, the application  202  may transmit the multiple images to server  206 . Additionally or alternatively, the application  202  may transmit to server  206  3-D data and scaling data, or at least one file associated with 3-D data and scaling data. 
     In some configurations, model generator  104  may process multiple images of a user to generate a 3-D model of the user. Model generator  104  may render a 3-D space that includes the 3-D model of the user and a 3-D polygon model of an object to render a virtual try-on 2-D image of the object and the user. The application  202  may output a display of the user to the display  108  while camera  106  captures an image of the user. 
       FIG. 3  is a block diagram illustrating one example of a model generator  104 - a . Model generator  104 - a  may be one example of model generator  104  depicted in  FIGS. 1  and/or  2 . As depicted, model generator  104 - a  may include a capturing module  302 , an image processor  304 , and a display module  306 . 
     In some configurations, the capturing module  302  may obtain a plurality of images of a user. In some embodiments, the capturing module  302  may activate camera  106  to capture at least one image of the user (e.g., a photograph). In some embodiments, the image processor  304  may process an image of the user captured by the capturing module  302 . The image processor  304  may be configured to generate a 3-D model of the user from the processing of the image. 
     In one embodiment, capturing module  302  may capture a plurality of images of a user, which may include photographs and or video images. In some embodiments, capturing module  302  may track a feature of the user in real time based at least in part on 3-D data derived from a set of previously captured and previously processed images. Capturing module  302  may capture a video of the user. In one example, capturing module  302  may capture images of a user (e.g., photographs). Image processor  304  may track one or more features of the real-time images of the user based on previously derived 3-D data of the user based on detected correlations between features of the real-time images of the user and corresponding features of the 3-D data. Display module  306  may display the real-time images and/or tracked features on a display in real time. 
     In one example, capturing module  302  may capture a first plurality of images. The first plurality of images may be processed prior to capturing a second plurality of images. In some cases, capturing module  302  may send the first plurality of images, including one or more scaling images, to a server for processing. Image processor  304  may process the plurality of images to generate 3-D data and/or scaling data. Model generator  104 - a  may receive the results of processing the first plurality of images and processing the one or more scaling images (e.g., 3-D data and/or scaling data). 
     In some embodiments, capturing module  302  may capture a second plurality of images subsequent to processing the first plurality of images. In one example, image processor  304  may generate a 3-D model of the user using the second plurality of images of the user in combination with the 3-D data derived from the first plurality of images of the user. Image processor  304  may detect an interest point in one or more of the second plurality of images and correlate the detected interest point with an interest point of the 3-D data. Image processor  304  may scale the 3-D model of the user using the scaling data derived from processing the one or more scaling images captured in conjunction with the capturing the first plurality of images. In some cases, image processor  304  may generate a first 3-D model of the user using the 3-D data derived from the first plurality of images, and generate a second 3-D model of the user using the second plurality of images and the same 3-D data derived from the first plurality of images. Display module  306  may display the first and/or second 3-D models on a display. In some embodiments, display module  306  may display 
       FIG. 4  illustrates an example arrangement  400  for capturing an image  404  of a user  402 . In particular, the illustrated example arrangement  400  may include the user  402  holding a device  102 - b . Device  102 - b  may include a camera  106 - a  and a display  108 - a . Device  102 - b , camera  106 - a , and display  108 - a  may be examples of device  102 , camera  106 , and display  108  depicted in  FIGS. 1  and/or  2 . 
     In one example, the user  402  holds device  102 - b  at arm&#39;s length with camera  106 - a  activated. Camera  106 - a  may capture an image  404  of the user and the display  108 - a  may show the captured image  404  to the user  402  (e.g., a real-time feedback image of the user). In some configurations, camera  106 - a  may capture a video of the user  402 . In some embodiments, the user may pan device  102 - b  around the user&#39;s face to allow camera  106 - a  to capture a video of the user from one side of the user&#39;s face to the other side of the user&#39;s face. Additionally, or alternatively, the user  402  may capture an image of other areas (e.g., arm, leg, torso, etc.). 
       FIG. 5  is a diagram  500  illustrating an example of a device  102 - c  for capturing an image  502  of a user. Device  102 - c  may be one example of device  102  illustrated in  FIGS. 1  and/or  2 . As depicted, device  102 - c  may include a camera  106 - b , a display  108 - b , and an application  202 - a . Camera  106 - b , display  108 - b , and application  202 - a  may each be an example of the respective camera  106 , display  108 , and application  202  illustrated in  FIGS. 1  and/or  2 . 
     In one embodiment, the user may operate device  102 - c . For example, the application  202 - a  may allow the user to interact with and/or operate device  102 - c . In one embodiment, the application  202 - a  may allow the user to capture an image  505  of the user. The display may show guidelines  504 - a  and  504 - b  to provide visual feedback to the user where to place the camera  106 - b  in relation to their face, etc. Application  202 - a  may display the captured image  502  on display  108 - b . In some cases, the application  202 - a  may permit the user to accept or decline the image  502  that was captured. In some embodiments, camera  106 - b  captures real-time images of the user and display  108 - b  shows the captured images (e.g. image  502 ) in real-time. Model generator  104  may track a feature of the real-time images of the user (e.g., facial features such as eyes, nose, mouth, etc.) based on 3-D data of the user derived from a previously captured plurality of images. 
       FIG. 6  illustrates an example arrangement  600  of a virtual 3-D space  602 . As depicted, the 3-D space  602  of the example arrangement  600  may include a 3-D model of a user&#39;s head  604 . In some embodiments, the 3-D model of the user&#39;s head  604  may include a polygon mesh model of the user&#39;s head, which may be stored in database  110  as 3-D data  112 . The 3-D data of the 3-D model of the user may include 3-D polygon mesh elements such as vertices, edges, faces, polygons, surfaces, and the like. Additionally, or alternatively, the 3-D model of the user&#39;s head  604  may include at least one texture map, which may be stored in the database  110 . 
       FIG. 7  is a flow diagram illustrating one embodiment of a method  700  for generating a 3-D model of a user. In some configurations, the method  700  may be implemented by model generator  104  illustrated in  FIGS. 1 ,  2 , and/or  3 . In some configurations, the method  700  may be implemented by the application  202  illustrated in  FIG. 2 . 
     At block  702 , a plurality of images of a user may be captured. At block  704 , a 3-D model of the user may be generated using the captured plurality of images of the user and 3-D data derived from a previously captured plurality of images of the user. 
       FIG. 8  is a flow diagram illustrating one embodiment of a method  800  for tracking a feature of the user in real-time. In some configurations, the method  800  may be implemented by model generator  104  illustrated in  FIGS. 1 ,  2 , and/or  3 . In some configurations, the method  700  may be implemented by the application  202  illustrated in  FIG. 2 . 
     At block  802 , a 3-D model of a user may be generated using a plurality of images of the user and 3-D data derived from a previous plurality of images of the user. At block  804 , a feature on the user may be identified in real-time based on the generated 3-D model of the user. At block  806  the identified feature of the user may be tracked in real-time. 
       FIG. 9  is a flow diagram illustrating one embodiment of a method  900  for displaying a feedback image to a user. In some configurations, the method  900  may be implemented by model generator  104  illustrated in  FIGS. 1 ,  2 , and/or  3 . In some configurations, the method  900  may be implemented by the application  202  illustrated in  FIG. 2 . 
     At block  902 , a first plurality of images of a user may be captured, including at least one scaling image. At block  904 , the first plurality of images may be processed in order to derive 3-D data from them. At block  906 , scaling data may be derived from the at least one scaling image. At block  908 , a first 3-D model may be generated from the 3-D data and scaling data. At block  910 , a second plurality of images of the user may be captured subsequent to processing the first plurality of images of the user. At block  912 , a second 3-D model of the user may be generated from both the second plurality of images and the 3-D data derived from the first plurality of images. 
       FIG. 10  depicts a block diagram of a computer system  1000  suitable for implementing the present systems and methods. Computer system  1010  includes a bus  1002  which interconnects major subsystems of computer system  1010 , such as a central processor  1014 , a system memory  1016  (typically RAM, but which may also include ROM, flash RAM, or the like), an input/output controller  1018 , an external audio device, such as a speaker system  1020  via an audio output interface  1022 , an external device, such as a display screen  1024  via display adapter  1026 , an keyboard  1032  (interfaced with a keyboard controller  1033 ) (or other input device), multiple USB devices  1092  (interfaced with a USB controller  1091 ), and a storage interface  1034 . Also included are a mouse  1046  (or other point-and-click device) and a network interface  1048  (coupled directly to bus  1002 ). 
     Bus  1002  allows data communication between central processor  1014  and system memory  1016 , which may include read-only memory (ROM) or flash memory (neither shown), and random access memory (RAM) (not shown), as previously noted. The RAM is generally the main memory into which the operating system and application programs are loaded. The ROM or flash memory can contain, among other code, the Basic Input-Output system (BIOS) which controls basic hardware operation such as the interaction with peripheral components or devices. For example, the rendering module  104 - b  to implement the present systems and methods may be stored within the system memory  1016 . Applications (e.g., application  202 ) resident with computer system  1010  are generally stored on and accessed via a non-transitory computer readable medium, such as a hard disk drive (e.g., fixed disk  1044 ) or other storage medium. Additionally, applications can be in the form of electronic signals modulated in accordance with the application and data communication technology when accessed via interface  1048 . 
     Storage interface  1034 , as with the other storage interfaces of computer system  1010 , can connect to a standard computer readable medium for storage and/or retrieval of information, such as a fixed disk drive  1044 . Fixed disk drive  1044  may be a part of computer system  1010  or may be separate and accessed through other interface systems. Network interface  1048  may provide a direct connection to a remote server via a direct network link to the Internet via a POP (point of presence). Network interface  1048  may provide such connection using wireless techniques, including digital cellular telephone connection, Cellular Digital Packet Data (CDPD) connection, digital satellite data connection, or the like. 
     Many other devices or subsystems (not shown) may be connected in a similar manner (e.g., document scanners, digital cameras, and so on). Conversely, all of the devices shown in  FIG. 10  need not be present to practice the present systems and methods. The devices and subsystems can be interconnected in different ways from that shown in  FIG. 10 . The operation of a computer system such as that shown in  FIG. 10  is readily known in the art and is not discussed in detail in this application. Code to implement the present disclosure can be stored in a non-transitory computer-readable medium such as one or more of system memory  1016  or fixed disk  1044 . The operating system provided on computer system  1010  may be iOS®, MS-DOS®, MS-WINDOWS®, OS/2®, UNIX®, Linux®, or another known operating system. 
     Moreover, regarding the signals described herein, those skilled in the art will recognize that a signal can be directly transmitted from a first block to a second block, or a signal can be modified (e.g., amplified, attenuated, delayed, latched, buffered, inverted, filtered, or otherwise modified) between the blocks. Although the signals of the above described embodiment are characterized as transmitted from one block to the next, other embodiments of the present systems and methods may include modified signals in place of such directly transmitted signals as long as the informational and/or functional aspect of the signal is transmitted between blocks. To some extent, a signal input at a second block can be conceptualized as a second signal derived from a first signal output from a first block due to physical limitations of the circuitry involved (e.g., there will inevitably be some attenuation and delay). Therefore, as used herein, a second signal derived from a first signal includes the first signal or any modifications to the first signal, whether due to circuit limitations or due to passage through other circuit elements which do not change the informational and/or final functional aspect of the first signal. 
     While the foregoing disclosure sets forth various embodiments using specific block diagrams, flowcharts, and examples, each block diagram component, flowchart step, operation, and/or component described and/or illustrated herein may be implemented, individually and/or collectively, using a wide range of hardware, software, or firmware (or any combination thereof) configurations. In addition, any disclosure of components contained within other components should be considered exemplary in nature since many other architectures can be implemented to achieve the same functionality. 
     The process parameters and sequence of steps described and/or illustrated herein are given by way of example only and can be varied as desired. For example, while the steps illustrated and/or described herein may be shown or discussed in a particular order, these steps do not necessarily need to be performed in the order illustrated or discussed. The various exemplary methods described and/or illustrated herein may also omit one or more of the steps described or illustrated herein or include additional steps in addition to those disclosed. 
     Furthermore, while various embodiments have been described and/or illustrated herein in the context of fully functional computing systems, one or more of these exemplary embodiments may be distributed as a program product in a variety of forms, regardless of the particular type of computer-readable media used to actually carry out the distribution. The embodiments disclosed herein may also be implemented using software modules that perform certain tasks. These software modules may include script, batch, or other executable files that may be stored on a computer-readable storage medium or in a computing system. In some embodiments, these software modules may configure a computing system to perform one or more of the exemplary embodiments disclosed herein. 
     The foregoing description, for purpose of explanation, has been described with reference to specific embodiments. However, the illustrative discussions above are not intended to be exhaustive or to limit the invention to the precise forms disclosed. Many modifications and variations are possible in view of the above teachings. The embodiments were chosen and described in order to best explain the principles of the present systems and methods and their practical applications, to thereby enable others skilled in the art to best utilize the present systems and methods and various embodiments with various modifications as may be suited to the particular use contemplated. 
     Unless otherwise noted, the terms “a” or “an,” as used in the specification and claims, are to be construed as meaning “at least one of.” In addition, for ease of use, the words “including” and “having,” as used in the specification and claims, are interchangeable with and have the same meaning as the word “comprising.” In addition, the term “based on” as used in the specification and the claims is to be construed as meaning “based at least upon.”