Patent Publication Number: US-2021192031-A1

Title: Motion-based credentials using magnified motion

Description:
CROSS REFERENCE TO RELATED APPLICATIONS 
     This application is a continuation of U.S. patent application Ser. No. 16/424,280, filed May 28, 2019, which is a continuation of U.S. patent application Ser. No. 14/957,303 filed Dec. 2, 2015, which issued as U.S. Pat. No. 10,303,863, issued May 28, 2019, which is a continuation of U.S. patent application Ser. No. 14/012,374 filed on Aug. 28, 2013, which issued as U.S. Pat. No. 9,213,817 on Dec. 15, 2015, all of which are incorporated by reference herein in their entirety. 
    
    
     BACKGROUND 
     Technical Field 
     Embodiments disclosed herein are related authentication systems and methods that magnify recorded motion for use as a motion-based credential. 
     Related Art 
     Traditional authentication using credentials may include entering credentials including a username and password such as a personal identification number (PIN) at a login screen, point-of-sale (POS), automated teller machine (ATM), and the like. However, these traditional authentication techniques have weaknesses and flaws that may be easily exploited by attackers. For example, so-called “shoulder-surfers” who are observers that can view the user&#39;s actions when entering a credential can learn the user&#39;s credentials by seeing the keys being pressed, password or PIN being entered on a screen, or even movements being made. To address these flaws, authentication systems may provide a cover to shield a user&#39;s hand from observation or not display or alter the a displayed credential after entry. 
    
    
     
       BRIEF DESCRIPTION OF THE FIGURES 
         FIG. 1  is a block diagram of a networked system, consistent with some embodiments. 
         FIG. 2  is a diagram illustrating a computing system, consistent with some embodiments. 
         FIG. 3  is a flowchart illustrating a method for performing Lagrangian motion magnification, according to a known embodiment. 
         FIG. 4  is a flowchart illustrating a method for performing Eulerian motion magnification, according to a known embodiment. 
         FIG. 5  is a diagram illustrating user authentication based on magnified motion, consistent with some embodiments. 
         FIG. 6  is a diagram illustrating authenticating at an automatic teller machine (ATM) using a motion-based credential, consistent with some embodiments. 
         FIG. 7  is a diagram illustrating a flow of authenticating using a motion-based credential, consistent with some embodiments. 
         FIG. 8  is a flowchart illustrating a process for authenticating using motion-based credentials, consistent with some embodiments. 
         FIG. 9  is a flowchart illustrating a process for authenticating using motion-based credentials, consistent with some embodiments. 
         FIG. 10  is a flowchart illustrating a process for authenticating using motion-based credentials, consistent with some embodiments. 
     
    
    
     In the drawings, elements having the same designation have the same or similar functions. 
     DETAILED DESCRIPTION 
     In the following description specific details are set forth describing certain embodiments. It will be apparent, however, to one skilled in the art that the disclosed embodiments may be practiced without some or all of these specific details. The specific embodiments presented are meant to be illustrative, but not limiting. One skilled in the art may realize other material that, although not specifically described herein, is within the scope and spirit of this disclosure. 
     There is a need for motion-based authentication systems and methods that rely on movements and motions that are very small or imperceptible to a bystander so that the motion or movement is not easily observable by a bystander. 
     Consistent with some embodiments, there is provided a system for authenticating using a motion-based credential. The system includes an image capture device configured to capture video of motion made by a user. The system also includes a memory storing the captured video and motion characteristics associated with the user. The system further includes one or more processors configured to process the captured video to magnify the motion made by the user, analyze the magnified motion to determine motion characteristics, and encrypt authentication information when the determined motion characteristics match the stored motion characteristics, the encrypted authentication information corresponding to the motion based credential. The system also includes a network interface component configured to send the encrypted authentication information for authenticating the user. 
     Consistent with some embodiments there is also provided a method for authenticating a user using a motion-based credential. The method includes steps of receiving a request to authenticate, prompting the user to make a motion, capturing a video of the motion, magnifying the motion in the captured video of the motion, and analyzing the magnified motion to determine characteristics of the motion, wherein the determined characteristics of the motion correspond to the motion-based credential and are used to authenticate the user. The method may also be embodied in computer-readable media. 
     Consistent with some embodiments, there is further provided a method for authenticating a user using a motion-based credential. The method includes steps of receiving an authentication request, sending a prompt for authentication information, receiving motion characteristics, the motion characteristics comprising characteristics of a magnified motion of the user, and authenticating the user when the received motion characteristics match stored motion characteristics associated with the user. The method may also be embodied in computer-readable media. 
     Embodiments consistent with this disclosure may allow authentication using movements and motions that may normally be very small or imperceptible to an observer by magnifying the motion, determining characteristics of the magnified motion, and using the magnified motion and the determined characteristics as a motion-based credential. 
       FIG. 1  is a block diagram of a networked system  100 , consistent with some embodiments. System  100  includes a client computing device  102  and a remote server  104  in communication over a network  106 . Remote server  104  may be a payment service provider server that may be maintained by a payment service provider, such as PayPal, Inc. of San Jose, Calif. Remote server  104  may be maintained by other service providers in different embodiments. Remote server  104  may also be maintained by an entity with which sensitive credentials and information may be exchanged with client computing device  102 . Remote server  104  may be more generally a web site, an online content manager, a service provider, such as a bank, or other entity who provides content to a user requiring user authentication or login. 
     Network  106 , in one embodiment, may be implemented as a single network or a combination of multiple networks. For example, in various embodiments, network  106  may include the Internet and/or one or more intranets, landline networks, wireless networks, and/or other appropriate types of communication networks. In another example, the network may comprise a wireless telecommunications network (e.g., cellular phone network) adapted to communicate with other communication networks, such as the Internet. 
     Client computing device  102 , in one embodiment, may be implemented using any appropriate combination of hardware and/or software configured for wired and/or wireless communication over network  106 . For example, client computing device  102  may be implemented as a wireless telephone (e.g., smart phone), tablet, personal digital assistant (PDA), notebook computer, personal computer, a connected set-top box (STB) such as provided by cable or satellite content providers, or a video game system console, a head-mounted display (HMD) or other wearable computing device, including a wearable computing device having an eyeglass projection screen, and/or various other generally known types of computing devices. 
     Client computing device  102  may include any appropriate combination of hardware and/or software having one or more processors and capable of reading instructions stored on a tangible non-transitory machine-readable medium for execution by the one or more processors. Consistent with some embodiments, client computing device  102  includes a machine-readable medium, such as a memory (not shown) that includes instructions for execution by one or more processors (not shown) for causing client computing device  102  to perform specific tasks. In some embodiments, the instructions may be executed by the one or more processors in response to interaction by user  108 . For example, such instructions may include browser application  110  such as a mobile browser application, which may be used to provide a user interface to permit user  108  to browse information available over network  106 , including information hosted by remote server  104 . For example, browser application  110  may be implemented as a web browser to view information available over network  106 . Browser application  110  may include a graphical user interface (GUI) that is configured to allow user  108  to interface and communicate with remote server  104  or other servers managed by content providers or merchants via network  106 . For example, user  108  may be able to access websites to find and purchase items, as well as access user account information or web content. 
     Client computing device  102  may also include an authentication application  112 . In some embodiments, authentication application  112  may prompt user  108  for one or more credentials for authenticating with remote server  104  and providing the credentials to remote server  104 . In some embodiments, authentication application  112  may be part of a payment application that may allow user  108  to authorize payments for goods and services (referred to collectively as “items”), with the payments being processed by remote server  106 . In some embodiments, authentication application  112  may prompt user  108  for one or more motion-based credentials which may be captured by client computing device  102  and analyzed for motion characteristics that are indicative of an identity of user  108 . Authentication application  112  may further include instructions for implementing a movement-based credential set-up procedure which may capture multiple initial movements of user  108  to establish a model or baseline of motion characteristics to which future authentication attempts using motion-based credentials may be matched. The established model or baseline may be stored in client computing device  102  for local matching or on remote server  104  for remote matching. 
     Client computing device  102  may also include a motion magnification application  114 . Motion magnification application  114  may include instructions and algorithms for magnifying motion captured for authenticating using movement-based credentials. In some embodiments, motion magnification application  114  may magnify selected areas of movement to magnify small, minor, normally imperceptible movements to be larger, more visible, and having significant characteristics for analysis. Motion magnification application  114  may use Euler magnification in some embodiments and Lagrangian magnification in some embodiments. In some embodiments, motion magnification application  114  may process captured video to magnify motion of user  108  for use by authentication application  112 , the magnified motion having certain observable and measurable characteristics that may be used to validate the identity of user  108  and authenticate user  108  with remote server  106 . Motion magnification application  114  may also execute in conjunction with authentication application  112  and, in some embodiments, execute as a background process. Client computing device  102  may include other applications  116  as may be desired in one or more embodiments to provide additional features available to user  108 , including accessing a user account with remote server  104 . For example, applications  116  may include interfaces and communication protocols that allow the user to receive and transmit information through network  106  and to remote server  104  and other online sites. Applications  116  may also include security applications for implementing client-side security features, programmatic client applications for interfacing with appropriate APIs over network  106  or various other types of generally known programs and/or applications. 
     Remote server  104 , according to some embodiments, may be maintained by an online payment provider or payment processor, such as PayPal, Inc. of San Jose, Calif., which may provide processing for online financial and information transactions on behalf of user  108 . Remote server  104  may include an authentication application  118  that, in some embodiments, may be in communication with authentication application  112  and motion magnification application  114  over network  106  for authenticating user  108  to remote server  104 . In some embodiments, authentication application  118  may receive one or more credentials provided by authentication application  112  of client computing device  102  for matching to credentials stored in user account information  120  in account database  122 . Such credentials may include motion-based credentials captured, processed, and analyzed by authentication application  112  and motion magnification application  114  of client computing device  102 . In some embodiments, authentication application  112  of client computing device  102  may capture motion-based credentials which may be magnified by motion magnification application  114 , and the magnified motion data may be provided to authentication application  118  of remote server for processing and analysis to validate user  108 . In some embodiments, motion magnification application  114  may be installed instead on remote server  104 , such that authentication application  112  may capture raw motion-based credentials and provide the raw data to remote server  104  for motion magnification and processing. Remote server  104  may include other applications  126  and may also be in communication with one or more external databases  128 , that may provide additional information that may be used by remote server  104 . In some embodiments, databases  128  may be databases maintained by third parties, and may include third party account information of user  108 . 
     Although discussion has been made of applications and applications on client computing device  102  and remote server  104 , the applications may also be, in some embodiments, modules. Module, as used herein, may refer to a software module that performs a function when executed by one or more processors or Application Specific Integrated Circuit (ASIC) or other circuit having memory and at least one processor for executing instructions to perform a function, such as the functions described as being performed by the applications. 
       FIG. 2  is a diagram illustrating computing system  200 , which may correspond to either of client computing device  102  or remote server  104 , consistent with some embodiments. Computing system  200  may be a mobile device such as a smartphone, a tablet computer, a personal computer, laptop computer, netbook, or tablet computer, set-top box, video game console, head-mounted display (HMD) or other wearable computing device as would be consistent with client computing device  102 . Further, computing system  200  may also be a server or one server amongst a plurality of servers, as would be consistent with remote server  104 . As shown in  FIG. 2 , computing system  200  includes a network interface component (NIC)  202  configured for communication with a network such as network  108  shown in  FIG. 1 . Consistent with some embodiments, NIC  202  includes a wireless communication component, such as a wireless broadband component, a wireless satellite component, or various other types of wireless communication components including radio frequency (RF), microwave frequency (MWF), and/or infrared (IR) components configured for communication with network  106 . Consistent with other embodiments, NIC  202  may be configured to interface with a coaxial cable, a fiber optic cable, a digital subscriber line (DSL) modem, a public switched telephone network (PSTN) modem, an Ethernet device, and/or various other types of wired and/or wireless network communication devices adapted for communication with network  106 . 
     Consistent with some embodiments, computing system  200  includes a system bus  204  for interconnecting various components within computing system  200  and communicating information between the various components. Such components include a processing component  206 , which may be one or more processors, micro-controllers, graphics processing units (GPUs) or digital signal processors (DSPs), and a memory component  208 , which may correspond to a random access memory (RAM), an internal memory component, a read-only memory (ROM), or an external or static optical, magnetic, or solid-state memory. Consistent with some embodiments, computing system  200  further includes a display component  210  for displaying information to a user  120  of computing system  200 . Display component  210  may be a liquid crystal display (LCD) screen, an organic light emitting diode (OLED) screen (including active matrix AMOLED screens), an LED screen, a plasma display, or a cathode ray tube (CRT) display. Computing system  200  may also include an input component  212 , allowing for a user of computing system  200 , such as consumer  120 , to input information to computing system  200 . Such information could include payment information such as an amount required to complete a transaction, account information, authentication information such as a credential, or identification information. An input component  212  may include, for example, a keyboard or key pad, whether physical or virtual. Computing system  200  may further include a navigation control component  214 , configured to allow a user to navigate along display component  210 . Consistent with some embodiments, navigation control component  214  may be a mouse, a trackball, or other such device. Moreover, if device  200  includes a touch screen, display component  210 , input component  212 , and navigation control  214  may be a single integrated component, such as a capacitive sensor-based touch screen. 
     Computing system  200  may further include a location component  216  for determining a location of computing system  200 . In some embodiments, location component  216  may correspond to a GPS transceiver that is in communication with one or more GPS satellites. In other embodiments, location component  216  may be configured to determine a location of computing system  200  by using an internet protocol (IP) address lookup, or by triangulating a position based on nearby telecommunications towers or wireless access points (WAPs). Location component  216  may be further configured to store a user-defined location in memory component  208  that can be transmitted to a third party for the purpose of identifying a location of computing system  200 . Computing system  200  may also include sensor components  218 . Sensor components  218  provide sensor functionality, and may correspond to sensors built into client computing device  102  or sensor peripherals coupled to client computing device  102 . Sensor components  218  may include any sensory device that captures information related to user  108  and/or client computing device  102  that may be associated with any actions that user  108  performs using client computing device  102 . Sensor components  218  may include accelerometers, biometric readers, GPS devices, and other devices that are capable of providing information about client computing device  102  or user  108 , or an environment therearound. 
     Computing system  200  may also include am imaging component  220 . In some embodiments, imaging component  220  may be an optical camera capable of capturing images. In some embodiments, the captured images may be a series of captured images, such as video frames. Imaging component  220  may be used by authentication application  112  of client computing device  102  to capture motion or movement by user  108  to use as motion-based credentials. 
     Computing system  200  may perform specific operations by processing component  206  executing one or more sequences of instructions contained memory component  208 . In other embodiments, hard-wired circuitry may be used in place of or in combination with software instructions to implement the present disclosure. Logic may be encoded in a computer readable medium, which may refer to any medium that participates in providing instructions to processing component  206  for execution, including memory component  208 . Consistent with some embodiments, the computer readable medium is tangible and non-transitory. In various implementations, non-volatile media include optical or magnetic disks, volatile media includes dynamic memory, and transmission media includes coaxial cables, copper wire, and fiber optics, including wires that comprise system bus  204 . According to some embodiments, transmission media may take the form of acoustic or light waves, such as those generated during radio wave and infrared data communications. Some common forms of computer readable media include, for example, floppy disk, flexible disk, hard disk, magnetic tape, any other magnetic medium, CD-ROM, any other optical medium, punch cards, paper tape, any other physical medium with patterns of holes, RAM, PROM, EPROM, FLASH-EPROM, any other memory chip or cartridge, carrier wave, or any other medium from which a computer is adapted to read. 
     In various embodiments of the present disclosure, execution of instruction sequences to practice the present disclosure may be performed by computing system  200 . In various other embodiments of the present disclosure, a plurality of computing systems  200  coupled by a communication link  222  to network  108  (e.g., such as a LAN, WLAN, PTSN, and/or various other wired or wireless networks, including telecommunications, mobile, and cellular phone networks) may perform instruction sequences to practice the present disclosure in coordination with one another. Computing system  200  may transmit and receive messages, data and one or more data packets, information and instructions, including one or more programs (i.e., application code) through communication link  222  and network interface component  202  and wireless transceiver  220 . Received program code may be executed by processing component  206  as received and/or stored in memory component  208 . 
       FIG. 3  is a flowchart illustrating a method for performing Lagrangian motion magnification, according to a known embodiment. As described above, motion magnification application  114  of client computing device  102  may perform Lagrangian motion magnification on captured video for magnifying selected areas of the captured video for analysis and identification of characteristics to use as motion-based credentials. Process  300  is a method for performing Lagrangian motion magnification as set forth in Liu, C., et al. “Motion Magnification,” ACM Transactions on Graphics (TOG)—Proceedings of ACM SIGGRAPH 2005, Vol. 24, Issue 3, July 2005, pages 519-526. As described therein, process  300  may analyze the motions of a video sequence such that a user can select a certain segment of pixels to be magnified. When the video is processed, the selected segment of pixels will have greatly exaggerated movements. As a result, movements which may normally appear very minor or even invisible to the human eye can be magnified such that the movements are perceptible in the processed video. 
     As shown in  FIG. 3 , process  300  begins by recording a video ( 302 ) and registering frames of the video ( 304 ) by performing an initial tracking of detected feature points in the recorded video and finding an affine warp which best removes the motions of the set of tracked feature points while ignoring outliers. Feature point trajectories may then be clustered ( 306 ) by grouping very small motions with larger motions to which they are correlated. Each pixel of each frame may then be assigned to a one of the feature point trajectory clusters ( 308 ) using motion, pixel color, and position to define a Markov random field. Each pixel trajectory may then be assigned to its most commonly assigned cluster over all time frames. A user may the select a particular cluster for motion magnification ( 310 ) and the selected cluster may then have its motion magnified ( 312 ) by amplifying all translations from the reference position by a constant amplification factor. The video having motion of the selected cluster magnified may then be rendered ( 314 ). The rendered motion magnified video may then include the selected cluster having magnified motion, which may be analyzed to determine the parameters of the magnified motion which, when not magnified, may be difficult to analyze from video. 
       FIG. 4  is a flowchart illustrating a method for performing Eulerian motion magnification, according to a known embodiment. As described above, motion magnification application  114  of client computing device  102  may perform Eulerian motion magnification on captured video for magnifying selected areas of the captured video for analysis and identification of characteristics to use as motion-based credentials. Process  400  is a method for performing Eulerian motion magnification as set forth in Wu, H. Y., et al. “Eulerian Video Magnification for Revealing Subtle Changes in the World,” ACM Transactions on Graphics (TOG)—SIGGRAPH 2012 Conference Proceedings, Vol. 31, Issue 4, July 2012, Article No. 65. As described therein, process  400  may perform spatial decomposition  402  on an input video  404  to decompose input video  404  into N different spatial frequency bands  406 - 1 - 406 -N. Each of the N-different spatial bands may then be temporally filtered by a temporal filter  408  to produce N-filtered bands  410 - 1 - 410 -N. Each of the N-filtered bands  410 - 1 - 410 -N may then be amplified by a given factor A N  by amplifiers  412 - 1 - 412 -N. The output of amplifiers  412 - 1 - 412 -N may be combined  414 - 1 - 414 -N with the unfiltered N-different spatial frequency bands  406 - 1 - 406 -N. The N combined outputs may then be reconstructed  416  to output a motion magnified video  418 . The combining  414 - 1 - 414 -N may include summing the amplified signals with the N-different spatial frequency bands  406 - 1 - 406 -N. Moreover, the choice of a temporal filter and amplification factor A N  may be tuned based on the particular application of process  400 . Similar to process  300 , process  400  may produce a motion magnified video  418 , which may be analyzed to determine the parameters of the magnified motion which, when not magnified, may be difficult to analyze from video. 
       FIG. 5  is a diagram illustrating user  108  authentication based on magnified motion, consistent with some embodiments. As discussed previously, authentication application  112  of client computing device  102  may prompt user  108  for one or more motion-based credentials which may be captured by client computing device  102  and analyzed for motion characteristics that are indicative of an identity of user  108 . In some embodiments, the motion-based credentials may correspond to very small finger movements. For example, as shown in  FIG. 5 , display component  210  of client computing device  102  may display an interface  500  requesting that user  108  enter a username  502  and a motion credential  504 , which may correspond to movements or motions made by flexing each finger on a hand  506  of user  108 . The flexing of the finger may be captured by imaging component  220  and magnified by motion magnification application  114  such that the magnified motion of the flexing of the fingers may be analyzed to verify an identity of user  108  and used to authenticate user  108  with remote server  104 . In some embodiments, motion magnification application  114  may use Lagrangian motion magnification, such as described with respect to  FIG. 3 , or Eulerian motion magnification, such as described with respect to  FIG. 4 . Moreover, although the movement of fingers is discussed as a motion-based credential in this embodiment, in other embodiments, other normally imperceptible motions may be magnified for use as a motion-based credential. Such motions may include eye movement, mouth movement, head movement, and the like. 
     Returning to  FIG. 5 , interface  500  requesting motion credential  504  may also include instructions for performing the motion that will be captured by imaging component  220 . Although not shown, client computing device  102  may also include a light such as a light emitting diode (LED), or a speaker configured to emit a tone, wherein the light will blink or the speaker will emit a tone when the user is supposed to perform the motion. The flashing light may also be provided by flashing display component  210  or rendering a flashing graphic on display component  210 . In some embodiments, the cue provided by the blinking light or audible tone may have a predetermined timing that may be used by motion magnification application  114  to correlate motions made by hand  506  to a timing of the captured video of hand  506 . For example, user  108  may be requested to move each finger of hand  506  starting with the little finger of hand  506  and ending with the thumb of hand  506  at predetermined intervals designated by an audible tone or blinking light. 
     The motion made by user  108  when entering the motion-based credential may then be captured by imaging component  220 , stored in memory component  208 , and processed by processing component  206  according to instructions specified in motion magnification application  114  to magnify the motion of the flexing of the fingers such that the motion is magnified to be capable of being analyzed to verify an identity of user  108  and used to authenticate user  108  with remote server  104 . 
     In some embodiments, the example of motion magnification shown in  FIG. 5  may be used to register motions of hand  506  to establish a baseline so that the registered motion may be used for comparison to subsequent motions that may be used, for example, to authenticate user  102  with remote server  104 . For example, when user  108  first uses authentication application  112 , user  108  may be required to perform motions, such as flexing fingers on hand  506 , of which video or other images may be captured and magnified for analysis. User  108  may be required to perform the motions multiple times until authentication application  112  has enough information from the magnified motions to establish a baseline from which subsequent motions can be compared. In some embodiments, authentication application  112  may establish a range of motion attributed to flexing a finger, such that a magnified motion of flexing an index finger exhibits a certain range of motion. In some embodiments, authentication application  112  may apply one or more machine-learning algorithms to the captured motions to predict what a motion of user  108  should be when magnified, based on the distance to imaging component  220 , the position of hand  506 , and other factors. Moreover, authentication application  112  may use a neural net to use fuzzy logic to attempt to match a magnified motion to an ideal or stored motion. 
     Once user  108  has successfully registered motions of hand  506 , user  108  may be able to use magnified motions of hand as a credential to authenticate with remote server  104 . In some embodiments, user  108  may be required to enter username  502  and then the registered motions may be captured and analyzed for use in authentication, in lieu of a password or personal identification number (PIN). In some embodiments, user  108  may not need to enter username  502 , as the magnified motions may be a sufficient credential unique to user  108 , similar to a biometric credential. In one example, a certain order of finger movement may correspond to a motion-based credential of user  108 . For example, the order may be thumb, little finger, ring finger, index finger, thumb. Any order of finger movements may make up the motion-based credential and may be assigned by authentication application  112  or  118 , or may be assigned by user  108 . Although the discussion with respect to  FIG. 5  has focused on magnifying the motions of a hand  506  of user  108 , in some embodiments other seemingly imperceptible or small movements or motions may be used for authentication. Such movements or motions may include moving (or wriggling) of the nose, tightening facial muscles, and the like. Consequently, by magnifying small or otherwise imperceptible movements made by user  108 , and magnifying these movements for the collection of real and meaningful data, user  108  may be able to authenticate with remote server  104  by making movements instead of entering passwords, PINs, and the like. 
       FIG. 6  is a diagram illustrating authenticating at an automatic teller machine (ATM)  600  using a motion-based credential, consistent with some embodiments. As shown in  FIG. 6 , client computing device  102  may correspond to an ATM such that user  108  may be capable of authenticating at the ATM using magnified motions. Typically, when user  108  interacts with ATM  600 , user  108  is required to enter their ATM card  602  into a card slot  602  on ATM  600  and enter a PIN. However, consistent with some embodiments, user  108  may be able to use a captured motion that has been magnified to interact with ATM  600 . Imaging component  220  of ATM  600  would capture images of user  108  moving fingers of hand  506  in a particular order unique to user  108 , and the captured images would have the movement of the fingers magnified for analysis and comparison with a registered motion previously captured to determine if the order of finger motions match the order that is assigned to user  108 . When the captured magnified motion matches the registered magnified motion, within a predetermined tolerance, user  506  may be able to interact with ATM  600  in the same way as if they had entered their PIN. 
     Additional examples of using motion-based credentials to authenticate may include make head movements in a particular order, such as left, right, forward, backward. These movements, if made small enough, would be normally imperceptible to observers but, when magnified by motion-magnification application, the movements may be analyzed to determine the order and direction of the movements. Another example would be clenching a jaw and even clenching a jaw in a certain direction in a certain order, or moving a nose up/left/right. In general, any motion that is normally small and imperceptible to a user may be magnified to be used as a motion-based credential. 
     In some embodiments, the magnified motion may be mapped to an action or command. For example, a small nearly imperceptible motion of a finger moving right to left may be magnified, and a motion vector of the movement clearly showing the right to left movement may be mapped to a swipe command. As another example, the motion of wriggling one&#39;s nose may be mapped to a page turn, such that when the motion is magnified, the motion vectors describing the motion can be clearly identified and used to indicate a page turn. Mapping the motion vectors determined from the magnified motion to actions or commands may provide additional accessibility and usability features to people having disabilities. 
       FIG. 7  is a diagram illustrating a flow of authenticating using a motion-based credential, consistent with some embodiments. As shown in  FIG. 7 , user  108  may initiate an authentication request using authentication application  112  on client computing device  102  for authenticating with remote server  104 . Authentication application  112  may request that user  108  provide a motion-based credential. If user  108  has not previously registered a motion for use as a motion-based credential, authentication application  112  may request that user  108  perform a series of motions to establish a motion-based credential. However, if user  108  has already registered a motion for use as a motion-based credential, user  108  may perform a motion as indicated by authentication application  112 . The performed motion may be captured by imaging component  220  of client computing device  102 . The captured motion may then be magnified by motion magnification application  114  to highlight and exaggerate the motion, which may be a motion that is otherwise very small or imperceptible. Authentication application  112  may then compare the magnified motion to a stored registered motion. Authentication application  112  may then encrypt the credential when there is a match and send the encrypted credential to remote server  104  for authentication. In some embodiments, the encrypted credential may include an encrypted user name, account number, or other datum that may be used by remote server  104  to identify user  108 . In some embodiments, the encrypted credential may also include information related to whether or not there was a match between the magnified performed motion and a stored magnified motion and a reliability indicator indicating the percent likelihood of a match. In some embodiments, if the motion-based credential includes a particular order of movements, the encrypted credential may include the order of movements. 
     In some embodiments, client computing device  102  may encrypt the captured motion, the magnified motion, or information related to an analysis of the magnified motion, and provide this information to remote server  104 . In such embodiments, remote server  104  may magnify the motion, analyze the magnified motion, and/or determine if there is a match between the magnified performed motion and stored magnified motion. Moreover, when determining if there is a match, the determination may include analyzing the magnified motion to determine if there is a match using a known pattern matching algorithms suitable for the motion being analyzed, Such algorithms may include analyzing motion vectors of the areas of magnified motion. 
       FIG. 8  is a flowchart illustrating a process  800  for authenticating using motion-based credentials, consistent with some embodiments. For the purpose of illustration,  FIG. 8  may be described with reference to any of  FIGS. 1-6 . Process  800  shown in  FIG. 8  may be embodied in computer-readable instructions for execution by one or more processors such that the steps of the method may be performed by client computing device  102 . As shown in  FIG. 8 , process  800  may begin when client computing device  102  receives an authentication request ( 802 ). In some embodiments, client computing device  102  may receive an authentication request when user  108  initiates an authentication request by activating or otherwise causing authentication application  112  to execute. Authentication application  112  may then prompt user  108  to make a motion ( 804 ). In some embodiments, the prompt may be displayed on display component  210  of client computing device  102 . Moreover, user  108  may have registered one or more motions or a specific order of motion for use as a motion-based credential and authentication application may prompt user  108  to make the same or similar motion as was previously registered. Further, prompting user  108  to make the motion may include displaying instructions for performing the motion and providing user  108  with a visual or audible cue for making the motion, such as may be provided by a flashing light or emitted tone. 
     Authentication application  112  may recording a video of user  108  performing the motion ( 806 ). In some embodiments, imaging component  220  of client computing device  102  may capture one or more images, which may be a series of images or frames such as a video, of user  108  performing the motion. Motion magnification application  114  may then process the recorded video to magnify the motion ( 808 ). In some embodiments, motion magnification application  114  may perform Lagrangian motion magnification or Eulerian motion magnification, or other motion magnification. Authentication application  112  may then analyze the processed video with magnified motion to determine motion characteristics ( 810 ). In some embodiments, the determined motion characteristics may include motion characteristics that may be used to verify the identity of user  108  and may include determining motion vectors of the magnified motion and the size, distance, and/or length of the determined motion vectors. 
     Authentication application  112  may then determine if the determined motion characteristics match stored motion characteristics ( 812 ). In some embodiments, determining if the determined motion characteristics match the stored motion characteristics may include analyzing motion vectors from the analyzed magnified motion match to those of stored motion vectors determined when user  108  registered the motion-based credential. In some embodiments, the determination may also include if a certain order of motions match a stored order of motions. In some embodiments, authentication application  112  may use a neural net to apply fuzzy logic to match the determined motion characteristics to stored motion characteristics. When the determined motion characteristics are determined to not match stored motion characteristics, user  108  may be prompted to make the motion again ( 804 ). In some embodiments, user  108  may be locked out of their account or asked to use a different form of authentication when a match is not made. When the determined motion characteristics match the stored authentication information, authentication application  112  may encrypt authentication information ( 814 ) and send the encrypted authentication information ( 816 ). In some embodiments, the encrypted authentication information may include an encrypted credential such as an encrypted user name, account number, or other datum that may be used to identify user  108 . In some embodiments, the encrypted credential may also include information related to whether or not there was a match between the magnified performed motion and a stored magnified motion and a reliability indicator indicating the percent likelihood of a match. The encrypted credential may also include an indication of an order in which motions were performed, such as left, left, right, for a directional motion-based credential or ring, index, middle, thumb, thumb, for a finger motion-based credential. Moreover, in some embodiments, the encrypted information may be sent to remote server  104  for authenticating user  108  with remote server  104 . 
       FIG. 9  is a flowchart illustrating a process  900  for authenticating using motion-based credentials, consistent with some embodiments. For the purpose of illustration,  FIG. 9  may be described with reference to any of  FIGS. 1-6 . Process  900  shown in  FIG. 9  may be embodied in computer-readable instructions for execution by one or more processors such that the steps of the method may be performed by client computing device  102 . Process  900  may be similar to process  800 , except in process  900  client computing device  102  determines motion characteristics, but does not determine if the motion characteristics match stored motion characteristics. Instead, client computing device encrypts the determined motion characteristics and provides them to remote server  104  which may have stored a registered motion-based credential with registered motion characteristics, and remote server  104  may perform the comparison to determine if there is a match. 
     As shown in  FIG. 9 , process  900  may begin when client computing device  102  receives an authentication request ( 902 ). In some embodiments, client computing device  102  may receive an authentication request when user  108  initiates an authentication request by activating or otherwise causing authentication application  112  to execute. Authentication application  112  may then prompt user  108  to make a motion ( 904 ). In some embodiments, the prompt may be displayed on display component  210  of client computing device  102 . Moreover, user  108  may have registered one or more motions for use as a motion-based credential and authentication application may prompt user  108  to make the same or similar motion as was previously registered or a certain order of motions. Further, prompting user  108  to make the motion may include displaying instructions for performing the motion and providing user  108  with a visual or audible cue for making the motion, such as may be provided by a flashing light or emitted tone. 
     Authentication application  112  may record a video of user  108  performing the motion ( 906 ). In some embodiments, imaging component  220  of client computing device  102  may capture one or more images, which may be a series of images or frames such as a video, of user  108  performing the motion. Motion magnification application  114  may then process the recorded video to magnify the motion ( 908 ). In some embodiments, motion magnification application  114  may perform Lagrangian motion magnification or Eulerian motion magnification, or other motion magnification. Authentication application  112  may then analyze the processed video with magnified motion to determine motion characteristics ( 910 ). In some embodiments, the determined motion characteristics may include motion characteristics that may be used to verify the identity of user  108  and may include determining motion vectors of the magnified motion and an order of motion. 
     Authentication application  112  may encrypt authentication the determined motion characteristics ( 912 ) and send the encrypted authentication motion characteristics ( 914 ). In some embodiments, the encrypted motion characteristics may be sent to remote server  104  for determining if the motion characteristics match stored motion characteristics associated with user  108  and authenticating user  108  with remote server  104  if there is a match. 
       FIG. 10  is a flowchart illustrating a process  1000  for authenticating using motion-based credentials, consistent with some embodiments. For the purpose of illustration,  FIG. 10  may be described with reference to any of  FIGS. 1-6 . Process  1000  shown in  FIG. 10  may be embodied in computer-readable instructions for execution by one or more processors such that the steps of the method may be performed by remote server  104 . Process  1000  may be similar to processes  800  and  900  except that remote server  104  receives an initial authentication request from client computing device  102  ( 1002 ) and then sends a prompt to client computing device  102  for authentication information ( 1004 ), the authentication information being a motion-based credential. In some embodiments, authentication application  118  of remote server  104  may cause the prompt for authentication information to be sent. Client computing device  102  may then record user  108  performing the motion, magnify the recorded motion, determine motion characteristics, and encrypt the determined motion characteristics, and send the encrypted determined motion characteristics to remote server  104 . 
     Process  1000  continues when remote server  104  receives the encrypted motion characteristics ( 1006 ) and decrypts the received motion characteristics ( 1008 ). Authentication application  118  of remote server  104  may then determine if the received motion characteristics match motion characteristics stored in account information  120  of account database  122 . In some embodiments, determining if the determined motion characteristics match the stored motion characteristics may include analyzing motion vectors from the analyzed magnified motion match to those of stored motion vectors determined when user  108  registered the motion-based credential. In some embodiments, the determination may also include if a certain order of motions match a stored order of motions. In some embodiments, authentication application  118  may use a neural net to apply fuzzy logic to attempt to match the motion characteristics to the stored motion characteristics. When the determined motion characteristics are determined to not match stored motion characteristics, authentication application  118  may send another prompt for authentication information ( 1004 ). In some embodiments, user  108  may be locked out of their account or asked to use a different form of authentication when a match is not made. When the determined motion characteristics match the stored authentication information, authentication application  118  may authenticate user  108  ( 1012 ). 
     Software, in accordance with the present disclosure, such as program code and/or data, may be stored on one or more machine-readable mediums, including non-transitory machine-readable medium. It is also contemplated that software identified herein may be implemented using one or more general purpose or specific purpose computers and/or computer systems, networked and/or otherwise. Where applicable, the ordering of various steps described herein may be changed, combined into composite steps, and/or separated into sub-steps to provide features described herein. 
     Embodiments described herein may allow authentication using movements and motions that may normally be very small or imperceptible to an observer by magnifying the motion, determining characteristics of the magnified motion, and using the magnified motion and the determined characteristics as a motion-based credential. The examples provided above are exemplary only and are not intended to be limiting. One skilled in the art may readily devise other systems consistent with the disclosed embodiments which are intended to be within the scope of this disclosure. As such, the application is limited only by the following claims.