Providing Hands-Free Data for Interactions

Abstract

A user verification system is configured to identify likely interactors approaching points of interaction to ensure accurate interactions and to provide loyalty rewards. In an example, a interaction system installs a user verification device with a stereo camera at an interacting device to capture images of the user and to obtain data from the device. The user verification device uses the stereo camera to determine the location of the user to determine if the user is a likely interactor. The user verification device recognizes motions of the user that are indicative of an interactor, such as reaching across the counter or looking at the operator. The user verification device identifies or verifies the interactor based on the record data or the display data. If the user is the likely interactor, then the system conducts a hands-free interaction with the user account or provides loyalty rewards to the user account.

1 - 20 . (canceled) 
     
     
         21 . A computer-implemented method to identify likely interactors approaching computing systems to perform an interaction, comprising:
 determining, by one or more computing devices based on image analysis of one or more images depicting a plurality of users, that a particular user of the plurality of users is in a position relative to a point of interaction including one or more merchant computing devices to be a likely transacting user based on a respective distance of the particular user from the point of interaction;   analyzing, by one or more computing devices, one or more motions made by the particular user of the plurality of users to determine if the one or more motions are indicative of a likely transacting user;   determining, by one or more computing devices, that the particular user is a likely interacting user based on the particular user being in the position relative to the point of interaction and the one or more motions made by the particular user being indicative of a likely transacting user; and   in response to determining that the particular user is a likely interacting user, generating, by the one or more computing devices, a notification that the particular user is interacting.   
     
     
         22 . The computer-implemented method of  claim 21 , further comprising:
 receiving, by one or more computing devices, the one or more images, wherein the one or more images are captured by a stereo camera; and   determining, by one or more computing devices, a respective distance from the point of interaction including the one or more merchant computing devices that each user of the plurality of users is located based on a triangulation of the one or more images.   
     
     
         23 . The computer-implemented method of  claim 22 , further comprising:
 configuring the stereo camera near the point of interaction including the one or more merchant computing devices.   
     
     
         24 . The method of  claim 22 , wherein determining the respective distance from the point of interaction that the particular user is located utilizes machine learning algorithms. 
     
     
         25 . The computer-implemented method of  claim 21 , further comprising:
 communicating, by one or more computing devices in response to determining that the particular user is the likely interacting user, a notification that the particular user is interacting.   
     
     
         26 . The computer-implemented method of  claim 21 , wherein the one or more motions of the particular user comprise one or more of approaching the point of interaction, reaching for a wallet, or reaching across a counter. 
     
     
         27 . The computer-implemented method of  claim 21 , further comprising:
 receiving, by one or more computing devices, a receipt from an interaction of the particular user;   analyzing, by one or more computing devices, the receipt to identify an account associated with the particular user; and   communicating, by one or more computing devices, a notification to an issuer of the account associated with the particular user of the interaction, the notification comprising data from the interaction.   
     
     
         28 . The computer-implemented method of  claim 27 , wherein the receipt is received from a communication sent to a receipt printer. 
     
     
         29 . The computer-implemented method of  claim 21 , further comprising:
 logging, by one or more computing devices, a beginning time of an interaction;   determining, by one or more computing devices, an appropriate time during the interaction to identify the particular user; and   identifying at the appropriate time, by one or more computing devices, the particular user is likely interacting.   
     
     
         30 . The computer-implemented method of  claim 29 , wherein determining an appropriate time comprises comparing a type of the interaction to a model of interactions of the type of the interaction to determine a time of the interaction in which an identification of the likely interacting user is most likely to be accurate. 
     
     
         31 . The computer-implemented method of  claim 21 , further comprising:
 performing, by one or more computing devices, facial recognition with respect to the particular user.   
     
     
         32 . The method of  claim 21 , wherein the one or more computing devices are associated with a merchant computing system. 
     
     
         33 . The method of  claim 21 , wherein the one or more computing devices operate on a point of sale terminal at a merchant location. 
     
     
         34 . The method of  claim 21 , further comprising:
 communicating, by one or more computing devices in response to determining that the particular user is the likely interacting user, a notification to a loyalty rewards system.   
     
     
         35 . One or more non-transitory computer-readable media having computer-executable program instructions embodied thereon that when executed by a computer cause the computer to perform operations, the operations comprising:
 determining, based on image analysis of one or more images depicting a plurality of users, that a particular user of the plurality of users is in a position relative to a point of interaction including one or more merchant computing devices to be a likely transacting user based on a respective distance of the particular user from the point of interaction;   analyzing one or more motions made by the particular user of the plurality of users to determine if the one or more motions are indicative of a likely transacting user;   determining that the particular user is a likely interacting user based on the particular user being in the position relative to the point of interaction and the one or more motions made by the particular user being indicative of a likely transacting user; and   in response to determining that the particular user is a likely interacting user, generating a notification that the particular user is interacting.   
     
     
         36 . The one or more non-transitory computer-readable media of  claim 35 , wherein the operations further comprise:
 receiving the one or more images, wherein the one or more images are captured by a stereo camera; and   determining a respective distance from the point of interaction including the one or more merchant computing devices that each user of the plurality of users is located based on a triangulation of the one or more images.   
     
     
         37 . The one or more non-transitory computer-readable media of  claim 35 , wherein the operations further comprise:
 communicating, in response to determining that the particular user is the likely interacting user, a notification that the particular user is interacting.   
     
     
         38 . A system to identify likely transactors approaching points of sale to ensure accurate transactions and to provide loyalty rewards, comprising:
 a processor communicatively coupled to a storage device and a network device, wherein the processor executes application code instructions that are stored in the storage device to cause the system to perform operations, the operations comprising:
 determining, based on image analysis of one or more images depicting a plurality of users, that a particular user of the plurality of users is in a position relative to a point of interaction including one or more merchant computing devices to be a likely transacting user based on a respective distance of the particular user from the point of interaction; 
 analyzing one or more motions made by the particular user of the plurality of users to determine if the one or more motions are indicative of a likely transacting user; 
 determining that the particular user is a likely interacting user based on the particular user being in the position relative to the point of interaction and the one or more motions made by the particular user being indicative of a likely transacting user; and 
 in response to determining that the particular user is a likely interacting user, generating a notification that the particular user is interacting. 
   
     
     
         39 . The system of  claim 38 , wherein the operations further comprise:
 receiving the one or more images, wherein the one or more images are captured by a stereo camera; and   determining a respective distance from the point of interaction including the one or more merchant computing devices that each user of the plurality of users is located based on a triangulation of the one or more images.   
     
     
         40 . The system of  claim 38 , wherein the operations further comprise:
 communicating, in response to determining that the particular user is the likely interacting user, a notification that the particular user is interacting.